title stringlengths 6 154 | authors stringlengths 5 1.96k | abstract stringlengths 392 2.86k ⌀ | pdf_path stringlengths 40 155 | bibtex stringlengths 213 2.79k | download_url stringlengths 87 201 |
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ReWeaver: Towards Simulation-Ready and Topology-Accurate Garment Reconstruction | Ming Li, Hui Shan, Kai Zheng, Chentao Shen, Siyu Liu, Yanwei Fu, Zhen Chen, Xiangru Huang | High-quality 3D garment reconstruction plays a crucial role in mitigating the sim-to-real gap in applications such as digital avatars, virtual try-on and robotic manipulation. However, existing garment reconstruction methods typically rely on unstructured representations, such as 3D Gaussian Splats, struggling to provi... | 2026/pdf/Li_ReWeaver_Towards_Simulation-Ready_and_Topology-Accurate_Garment_Reconstruction_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Ming and Shan, Hui and Zheng, Kai and Shen, Chentao and Liu, Siyu and Fu, Yanwei and Chen, Zhen and Huang, Xiangru},
title = {ReWeaver: Towards Simulation-Ready and Topology-Accurate Garment Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conferenc... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_ReWeaver_Towards_Simulation-Ready_and_Topology-Accurate_Garment_Reconstruction_CVPR_2026_paper.pdf |
Scan Clusters, Not Pixels: A Cluster-Centric Paradigm for Efficient Ultra-high-definition Image Restoration | Chen Wu, Ling Wang, Zhuoran Zheng, Yuning Cui, Zhixiong Yang, Xiangyu Chen, Yue Zhang, Weidong Jiang, Jingyuan Xia | Ultra-High-Definition (UHD) image restoration is trapped in a scalability crisis: existing models, bound to pixel-wise operations, demand unsustainable computation. While state space models (SSMs) like Mamba promise linear complexity, their pixel-serial scanning remains a fundamental bottleneck for the millions of pixe... | 2026/pdf/Wu_Scan_Clusters_Not_Pixels_A_Cluster-Centric_Paradigm_for_Efficient_Ultra-high-definition_CVPR_2026_paper.pdf | @InProceedings{Wu_2026_CVPR,
author = {Wu, Chen and Wang, Ling and Zheng, Zhuoran and Cui, Yuning and Yang, Zhixiong and Chen, Xiangyu and Zhang, Yue and Jiang, Weidong and Xia, Jingyuan},
title = {Scan Clusters, Not Pixels: A Cluster-Centric Paradigm for Efficient Ultra-high-definition Image Restoration... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wu_Scan_Clusters_Not_Pixels_A_Cluster-Centric_Paradigm_for_Efficient_Ultra-high-definition_CVPR_2026_paper.pdf |
PETAR: Localized Findings Generation with Mask-Aware Vision-Language Modeling for PET Automated Reporting | Danyal Maqbool, Changhee Lee, Zachary Huemann, Samuel D. Church, Matthew E. Larson, Scott B. Perlman, Tomas A. Romero, Joshua D. Warner, Meghan Lubner, Xin Tie, Jameson Merkow, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw | Generating automated reports for 3D positron emission tomography (PET) is an important and challenging task in medical imaging. PET plays a vital role in oncology, but automating report generation is difficult due to the complexity of whole-body 3D volumes, the wide range of potential clinical findings, and the limited... | 2026/pdf/Maqbool_PETAR_Localized_Findings_Generation_with_Mask-Aware_Vision-Language_Modeling_for_PET_CVPR_2026_paper.pdf | @InProceedings{Maqbool_2026_CVPR,
author = {Maqbool, Danyal and Lee, Changhee and Huemann, Zachary and Church, Samuel D. and Larson, Matthew E. and Perlman, Scott B. and Romero, Tomas A. and Warner, Joshua D. and Lubner, Meghan and Tie, Xin and Merkow, Jameson and Hu, Junjie and Cho, Steve Y. and Bradshaw, Tyler... | https://openaccess.thecvf.com/content/CVPR2026/papers/Maqbool_PETAR_Localized_Findings_Generation_with_Mask-Aware_Vision-Language_Modeling_for_PET_CVPR_2026_paper.pdf |
SPARROW: Learning Spatial Precision and Temporal Referential Consistency in Pixel-Grounded Video MLLMs | Mohamad Alansari, Naufal Suryanto, Divya Velayudhan, Sajid Javed, Naoufel Werghi, Muzammal Naseer | Multimodal large language models (MLLMs) have advanced from image-level reasoning to pixel-level grounding, but extending these capabilities to videos remains challenging as models must achieve spatial precision and temporally consistent reference tracking. Existing video MLLMs often rely on a static segmentation token... | 2026/pdf/Alansari_SPARROW_Learning_Spatial_Precision_and_Temporal_Referential_Consistency_in_Pixel-Grounded_CVPR_2026_paper.pdf | @InProceedings{Alansari_2026_CVPR,
author = {Alansari, Mohamad and Suryanto, Naufal and Velayudhan, Divya and Javed, Sajid and Werghi, Naoufel and Naseer, Muzammal},
title = {SPARROW: Learning Spatial Precision and Temporal Referential Consistency in Pixel-Grounded Video MLLMs},
booktitle = {Proceedi... | https://openaccess.thecvf.com/content/CVPR2026/papers/Alansari_SPARROW_Learning_Spatial_Precision_and_Temporal_Referential_Consistency_in_Pixel-Grounded_CVPR_2026_paper.pdf |
Iterative Closed-Loop Motion Synthesis for Scaling the Capabilities of Humanoid Control | Weisheng Xu, Qiwei Wu, Jiaxi Zhang, Jing Tan, Yangfan Li, Yuetong Fang, Jiaqi Xiong, Kai Wu, Rong Ou, Renjing Xu | Physics-based humanoid control relies on training with motion datasets that have diverse data distributions. However, the fixed difficulty distribution of datasets limits the performance ceiling of the trained control policies. Additionally, the method of acquiring high-quality data through professional motion capture ... | 2026/pdf/Xu_Iterative_Closed-Loop_Motion_Synthesis_for_Scaling_the_Capabilities_of_Humanoid_CVPR_2026_paper.pdf | @InProceedings{Xu_2026_CVPR,
author = {Xu, Weisheng and Wu, Qiwei and Zhang, Jiaxi and Tan, Jing and Li, Yangfan and Fang, Yuetong and Xiong, Jiaqi and Wu, Kai and Ou, Rong and Xu, Renjing},
title = {Iterative Closed-Loop Motion Synthesis for Scaling the Capabilities of Humanoid Control},
booktitle =... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xu_Iterative_Closed-Loop_Motion_Synthesis_for_Scaling_the_Capabilities_of_Humanoid_CVPR_2026_paper.pdf |
PROMPTMINER: Black-Box Prompt Stealing against Text-to-Image Generative Models via Reinforcement Learning and VLM-Guided Optimization | Mingzhe Li, Renhao Zhang, Zhiyang Wen, Siqi Pan, Bruno Castro da Silva, Juan Zhai, Shiqing Ma | Text-to-image (T2I) generative models such as Stable Diffusion and FLUX can synthesize realistic, high-quality images directly from textual prompts. The resulting image quality depends critically on well-crafted prompts that specify both subjects and stylistic modifiers, which have become valuable digital assets. Howev... | 2026/pdf/Li_PROMPTMINER_Black-Box_Prompt_Stealing_against_Text-to-Image_Generative_Models_via_Reinforcement_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Mingzhe and Zhang, Renhao and Wen, Zhiyang and Pan, Siqi and da Silva, Bruno Castro and Zhai, Juan and Ma, Shiqing},
title = {PROMPTMINER: Black-Box Prompt Stealing against Text-to-Image Generative Models via Reinforcement Learning and VLM-Guided Optimization},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_PROMPTMINER_Black-Box_Prompt_Stealing_against_Text-to-Image_Generative_Models_via_Reinforcement_CVPR_2026_paper.pdf |
Editprint: General Digital Image Forensics via Editing Fingerprint with Self-Augmentation Training | Haiwei Wu, Kemou Li, Yuanman Li, Jiantao Zhou | Digital image forensics can ensure information credibility in tasks like camera source identification (CSI), synthetic image detection (SID), and social network provenance (SNP). These tasks typically rely on image processing history clues left by in-camera operations, post-capture editing, or synthetic generation. How... | 2026/pdf/Wu_Editprint_General_Digital_Image_Forensics_via_Editing_Fingerprint_with_Self-Augmentation_CVPR_2026_paper.pdf | @InProceedings{Wu_2026_CVPR,
author = {Wu, Haiwei and Li, Kemou and Li, Yuanman and Zhou, Jiantao},
title = {Editprint: General Digital Image Forensics via Editing Fingerprint with Self-Augmentation Training},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognit... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wu_Editprint_General_Digital_Image_Forensics_via_Editing_Fingerprint_with_Self-Augmentation_CVPR_2026_paper.pdf |
Routing on Demand: DSNet for Efficient Progressive Point Cloud Denoising | Xiaoqian Cheng, Dong Xiao, Husen Li, Zheng Liu, Renjie Chen | Point cloud denoising is a critical preprocessing step for enhancing the reliability and accuracy of 3D perception systems. Most existing progressive denoising methods rely on fixed iterative pipelines that process all regions uniformly, resulting in redundant computation and over-smoothing of geometric details when ha... | 2026/pdf/Cheng_Routing_on_Demand_DSNet_for_Efficient_Progressive_Point_Cloud_Denoising_CVPR_2026_paper.pdf | @InProceedings{Cheng_2026_CVPR,
author = {Cheng, Xiaoqian and Xiao, Dong and Li, Husen and Liu, Zheng and Chen, Renjie},
title = {Routing on Demand: DSNet for Efficient Progressive Point Cloud Denoising},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (... | https://openaccess.thecvf.com/content/CVPR2026/papers/Cheng_Routing_on_Demand_DSNet_for_Efficient_Progressive_Point_Cloud_Denoising_CVPR_2026_paper.pdf |
When Lines Meet Textures: Spatial-Frequency Aligned Diffusion Features for Cross-Sparsity Correspondence | Mingrui Zhu, Fengzhi Wang, Xin Wei, Jun Wang, Nannan Wang, Xinbo Gao | Establishing accurate correspondence between sparse line representations and rich textured imagery remains a formidable challenge. While diffusion features excel in semantic correspondence, they struggle to bridge the fundamental gap between abstract sketches and texture-rich photographs. We identify two critical dispa... | 2026/pdf/Zhu_When_Lines_Meet_Textures_Spatial-Frequency_Aligned_Diffusion_Features_for_Cross-Sparsity_CVPR_2026_paper.pdf | @InProceedings{Zhu_2026_CVPR,
author = {Zhu, Mingrui and Wang, Fengzhi and Wei, Xin and Wang, Jun and Wang, Nannan and Gao, Xinbo},
title = {When Lines Meet Textures: Spatial-Frequency Aligned Diffusion Features for Cross-Sparsity Correspondence},
booktitle = {Proceedings of the IEEE/CVF Conference o... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhu_When_Lines_Meet_Textures_Spatial-Frequency_Aligned_Diffusion_Features_for_Cross-Sparsity_CVPR_2026_paper.pdf |
S2D: Selective Spectral Decay for Quantization-Friendly Conditioning of Neural Activations | Arnav Chavan, Nahush Lele, Udbhav Bamba, Sankalp Dayal, Aditi Raghunathan, Deepak Gupta | Activation outliers in large-scale transformer models pose a fundamental challenge to model quantization, creating excessively large ranges that cause severe accuracy drops during quantization. We empirically observe that outlier severity intensifies with pre-training scale (e.g., progressing from CLIP to the more exte... | 2026/pdf/Chavan_S2D_Selective_Spectral_Decay_for_Quantization-Friendly_Conditioning_of_Neural_Activations_CVPR_2026_paper.pdf | @InProceedings{Chavan_2026_CVPR,
author = {Chavan, Arnav and Lele, Nahush and Bamba, Udbhav and Dayal, Sankalp and Raghunathan, Aditi and Gupta, Deepak},
title = {S2D: Selective Spectral Decay for Quantization-Friendly Conditioning of Neural Activations},
booktitle = {Proceedings of the IEEE/CVF Conf... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chavan_S2D_Selective_Spectral_Decay_for_Quantization-Friendly_Conditioning_of_Neural_Activations_CVPR_2026_paper.pdf |
Pushing the Frontier of Audiovisual Perception with Large-Scale Multimodal Correspondence Learning | Apoorv Vyas, Heng-Jui Chang, Cheng-Fu Yang, Po-Yao Huang, Luya Gao, Julius Richter, Sanyuan Chen, Matthew Le, Piotr Dollár, Christoph Feichtenhofer, Ann Lee, Wei-Ning Hsu | We introduce Perception Encoder-Audiovisual, PE-AV, a new family of encoders for audio and video understanding trained with scaled contrastive learning. Building on PE, PE-AV makes several key contributions to extend representations to audio, and natively support joint embeddings across audio-video, audio-text, and vid... | 2026/pdf/Vyas_Pushing_the_Frontier_of_Audiovisual_Perception_with_Large-Scale_Multimodal_Correspondence_CVPR_2026_paper.pdf | @InProceedings{Vyas_2026_CVPR,
author = {Vyas, Apoorv and Chang, Heng-Jui and Yang, Cheng-Fu and Huang, Po-Yao and Gao, Luya and Richter, Julius and Chen, Sanyuan and Le, Matthew and Doll\'ar, Piotr and Feichtenhofer, Christoph and Lee, Ann and Hsu, Wei-Ning},
title = {Pushing the Frontier of Audiovisual... | https://openaccess.thecvf.com/content/CVPR2026/papers/Vyas_Pushing_the_Frontier_of_Audiovisual_Perception_with_Large-Scale_Multimodal_Correspondence_CVPR_2026_paper.pdf |
ElasticFormer: Detecting Objects in HRW Shots via Elastic Computing Vision Transformer | Wenxi Li, Jingchen Huang, Chenyang Lyu, Moran Liu, Haozhe Lin, Guiguang Ding, Yuchen Guo | Recent advances in gigapixel-level imaging have brought High-Resolution Wide shots to the forefront of research. However, these images present significant challenges: extreme sparsity of foreground, gigapixel-level resolutions and diverse target counts. This makes traditional close-up detectors inaccurate and slow as ... | 2026/pdf/Li_ElasticFormer_Detecting_Objects_in_HRW_Shots_via_Elastic_Computing_Vision_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Wenxi and Huang, Jingchen and Lyu, Chenyang and Liu, Moran and Lin, Haozhe and Ding, Guiguang and Guo, Yuchen},
title = {ElasticFormer: Detecting Objects in HRW Shots via Elastic Computing Vision Transformer},
booktitle = {Proceedings of the IEEE/CVF Confere... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_ElasticFormer_Detecting_Objects_in_HRW_Shots_via_Elastic_Computing_Vision_CVPR_2026_paper.pdf |
NS-Diff: Fluid Navier-Stokes Guided Video Diffusion via Reinforcement Learning | Zijun Deng, Yuxin Peng | While recent video generation models achieve impressive visual quality, generating physically plausible videos remains challenging, especially for fluid dynamics and rigid-body motions. To address this, we present **NS-Diff**, a physics-guided reinforcement learning framework for video diffusion. First, we design a noi... | 2026/pdf/Deng_NS-Diff_Fluid_Navier-Stokes_Guided_Video_Diffusion_via_Reinforcement_Learning_CVPR_2026_paper.pdf | @InProceedings{Deng_2026_CVPR,
author = {Deng, Zijun and Peng, Yuxin},
title = {NS-Diff: Fluid Navier-Stokes Guided Video Diffusion via Reinforcement Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Deng_NS-Diff_Fluid_Navier-Stokes_Guided_Video_Diffusion_via_Reinforcement_Learning_CVPR_2026_paper.pdf |
PhysGaia: A Physics-aware Benchmark with Multi-Body Interactions for Dynamic Novel View Synthesis | Mijeong Kim, Gunhee Kim, Jungyoon Choi, Wonjae Roh, Bohyung Han | We introduce PhysGaia, a novel physics-aware benchmark for Dynamic Novel View Synthesis (DyNVS) that encompasses both structured objects and unstructured physical phenomena. While existing datasets primarily focus on photorealistic appearance, PhysGaia is specifically designed to support physics-consistent dynamic reco... | 2026/pdf/Kim_PhysGaia_A_Physics-aware_Benchmark_with_Multi-Body_Interactions_for_Dynamic_Novel_CVPR_2026_paper.pdf | @InProceedings{Kim_2026_CVPR,
author = {Kim, Mijeong and Kim, Gunhee and Choi, Jungyoon and Roh, Wonjae and Han, Bohyung},
title = {PhysGaia: A Physics-aware Benchmark with Multi-Body Interactions for Dynamic Novel View Synthesis},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Visio... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kim_PhysGaia_A_Physics-aware_Benchmark_with_Multi-Body_Interactions_for_Dynamic_Novel_CVPR_2026_paper.pdf |
CaliTex: Geometry-Calibrated Attention for View-Coherent 3D Texture Generation | Chenyu Liu, Hongze Chen, Jingzhi Bao, Lingting Zhu, Runze Zhang, Weikai Chen, Zeyu Hu, Yingda Yin, Keyang Luo, Xin Wang | Despite major advances brought by diffusion-based models, current 3D texture generation systems remain hindered by cross-view inconsistency -- textures that appear convincing from one viewpoint often fail to align across others. We find that this issue arises from attention ambiguity, where unstructured full attention ... | 2026/pdf/Liu_CaliTex_Geometry-Calibrated_Attention_for_View-Coherent_3D_Texture_Generation_CVPR_2026_paper.pdf | @InProceedings{Liu_2026_CVPR,
author = {Liu, Chenyu and Chen, Hongze and Bao, Jingzhi and Zhu, Lingting and Zhang, Runze and Chen, Weikai and Hu, Zeyu and Yin, Yingda and Luo, Keyang and Wang, Xin},
title = {CaliTex: Geometry-Calibrated Attention for View-Coherent 3D Texture Generation},
booktitle = ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Liu_CaliTex_Geometry-Calibrated_Attention_for_View-Coherent_3D_Texture_Generation_CVPR_2026_paper.pdf |
DynamicTree: Interactive Real Tree Animation via Sparse Voxel Spectrum | Yaokun Li, Lihe Ding, Xiao Chen, Guang Tan, Tianfan Xue | Generating dynamic and interactive 3D trees has wide applications in virtual reality, games, and world simulation. However, existing methods still face various challenges in generating structurally consistent and realistic 4D motion for complex real trees. In this paper, we propose DynamicTree, the first framework that... | 2026/pdf/Li_DynamicTree_Interactive_Real_Tree_Animation_via_Sparse_Voxel_Spectrum_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Yaokun and Ding, Lihe and Chen, Xiao and Tan, Guang and Xue, Tianfan},
title = {DynamicTree: Interactive Real Tree Animation via Sparse Voxel Spectrum},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_DynamicTree_Interactive_Real_Tree_Animation_via_Sparse_Voxel_Spectrum_CVPR_2026_paper.pdf |
Ghost-FWL: A Large-Scale Full-Waveform LiDAR Dataset for Ghost Detection and Removal | Kazuma Ikeda, Ryosei Hara, Rokuto Nagata, Ozora Sako, Zihao Ding, Takahiro Kado, Ibuki Fujioka, Taro Beppu, Mariko Isogawa, Kentaro Yoshioka | LiDAR has become an essential sensing modality in autonomous driving, robotics, and smart-city applications. However, ghost points (or ghost), which are false reflections caused by multi-path laser returns from glass and reflective surfaces, severely degrade 3D mapping and localization accuracy. Prior ghost removal rel... | 2026/pdf/Ikeda_Ghost-FWL_A_Large-Scale_Full-Waveform_LiDAR_Dataset_for_Ghost_Detection_and_CVPR_2026_paper.pdf | @InProceedings{Ikeda_2026_CVPR,
author = {Ikeda, Kazuma and Hara, Ryosei and Nagata, Rokuto and Sako, Ozora and Ding, Zihao and Kado, Takahiro and Fujioka, Ibuki and Beppu, Taro and Isogawa, Mariko and Yoshioka, Kentaro},
title = {Ghost-FWL: A Large-Scale Full-Waveform LiDAR Dataset for Ghost Detection a... | https://openaccess.thecvf.com/content/CVPR2026/papers/Ikeda_Ghost-FWL_A_Large-Scale_Full-Waveform_LiDAR_Dataset_for_Ghost_Detection_and_CVPR_2026_paper.pdf |
Yo'City: Personalized and Boundless 3D Realistic City Scene Generation via Self-Critic Expansion | Keyang Lu, Sifan Zhou, Hongbin Xu, Gang Xu, Zhifei Yang, Yikai Wang, Zhen Xiao, Jieyi Long, Ming Li | Realistic 3D city generation is fundamental to a wide range of applications, including virtual reality and digital twins. However, most existing methods rely on training a single diffusion model, which limits their ability to generate personalized and boundless city-scale scenes. In this paper, we present Yo'City, a no... | 2026/pdf/Lu_YoCity_Personalized_and_Boundless_3D_Realistic_City_Scene_Generation_via_CVPR_2026_paper.pdf | @InProceedings{Lu_2026_CVPR,
author = {Lu, Keyang and Zhou, Sifan and Xu, Hongbin and Xu, Gang and Yang, Zhifei and Wang, Yikai and Xiao, Zhen and Long, Jieyi and Li, Ming},
title = {Yo'City: Personalized and Boundless 3D Realistic City Scene Generation via Self-Critic Expansion},
booktitle = {Procee... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lu_YoCity_Personalized_and_Boundless_3D_Realistic_City_Scene_Generation_via_CVPR_2026_paper.pdf |
LVLM-Aided Alignment of Task-Specific Vision Models | Alexander Koebler, Lukas Kuhn, Ingo Thon, Florian Buettner | In high-stakes domains, small task-specific vision models are crucial due to their low computational requirements and the availability of numerous methods to explain their results. However, these explanations often reveal that the models do not align well with human domain knowledge, relying instead on spurious correla... | 2026/pdf/Koebler_LVLM-Aided_Alignment_of_Task-Specific_Vision_Models_CVPR_2026_paper.pdf | @InProceedings{Koebler_2026_CVPR,
author = {Koebler, Alexander and Kuhn, Lukas and Thon, Ingo and Buettner, Florian},
title = {LVLM-Aided Alignment of Task-Specific Vision Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Koebler_LVLM-Aided_Alignment_of_Task-Specific_Vision_Models_CVPR_2026_paper.pdf |
Unified Latent Space for Understanding and Generation via Semantic Auto-encoder | Xiaojie Li, Yang Zhao, Ming Li, Yancheng Zhang, Zonglin Lyu, Yunpeng Chen, Rui Wang, Daquan Zhou | Latent generative modeling has emerged as the dominant paradigm for Diffusion Transformers (DiT), where a pretrained autoencoder compresses image pixels into a latent space to facilitate the diffusion process. Recently, the use of semantic encoders within autoencoders (AEs) has gained attention, yet their influence on ... | 2026/pdf/Li_Unified_Latent_Space_for_Understanding_and_Generation_via_Semantic_Auto-encoder_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Xiaojie and Zhao, Yang and Li, Ming and Zhang, Yancheng and Lyu, Zonglin and Chen, Yunpeng and Wang, Rui and Zhou, Daquan},
title = {Unified Latent Space for Understanding and Generation via Semantic Auto-encoder},
booktitle = {Proceedings of the IEEE/CVF Co... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_Unified_Latent_Space_for_Understanding_and_Generation_via_Semantic_Auto-encoder_CVPR_2026_paper.pdf |
Detecting Unknown Objects via Energy-based Separation for Open World Object Detection | Jun-Woo Heo, Keonhee Park, Gyeong-Moon Park | In this work, we tackle the problem of Open World Object Detection (OWOD). This challenging scenario requires the detector to incrementally learn to classify known objects without forgetting while identifying unknown objects without supervision. Previous OWOD methods have enhanced the unknown discovery process and empl... | 2026/pdf/Heo_Detecting_Unknown_Objects_via_Energy-based_Separation_for_Open_World_Object_CVPR_2026_paper.pdf | @InProceedings{Heo_2026_CVPR,
author = {Heo, Jun-Woo and Park, Keonhee and Park, Gyeong-Moon},
title = {Detecting Unknown Objects via Energy-based Separation for Open World Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
m... | https://openaccess.thecvf.com/content/CVPR2026/papers/Heo_Detecting_Unknown_Objects_via_Energy-based_Separation_for_Open_World_Object_CVPR_2026_paper.pdf |
EpiAgent: An Agent-Centric System for Ancient Inscription Restoration | Shipeng Zhu, Ang Chen, Na Nie, Pengfei Fang, Min-Ling Zhang, Hui Xue | Ancient inscriptions, as repositories of cultural memory, have suffered from centuries of environmental and human-induced degradation. Restoring their intertwined visual and textual integrity poses one of the most demanding challenges in digital heritage preservation. However, existing AI-based approaches often rely on... | 2026/pdf/Zhu_EpiAgent_An_Agent-Centric_System_for_Ancient_Inscription_Restoration_CVPR_2026_paper.pdf | @InProceedings{Zhu_2026_CVPR,
author = {Zhu, Shipeng and Chen, Ang and Nie, Na and Fang, Pengfei and Zhang, Min-Ling and Xue, Hui},
title = {EpiAgent: An Agent-Centric System for Ancient Inscription Restoration},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhu_EpiAgent_An_Agent-Centric_System_for_Ancient_Inscription_Restoration_CVPR_2026_paper.pdf |
DiGraphHal-Bench: Evaluating Multimodal Large Language Models on Complex Directed Graphs | Yixin Fan, Zhao He, Yuxin Hou, Changhua Zhou, Zihao Liu, Peng Wang, Chenglong Lu, Xu Zhang, Wei Wang | While prior research on Multimodal Large Language Model (MLLM) hallucinations has primarily examined cross-modal inconsistencies in natural images, hallucination over complex graph structures remains underexplored.Concurrently, there is a lack of robust evaluation for fine-grained reasoning integrating structural, visu... | 2026/pdf/Fan_DiGraphHal-Bench_Evaluating_Multimodal_Large_Language_Models_on_Complex_Directed_Graphs_CVPR_2026_paper.pdf | @InProceedings{Fan_2026_CVPR,
author = {Fan, Yixin and He, Zhao and Hou, Yuxin and Zhou, Changhua and Liu, Zihao and Wang, Peng and Lu, Chenglong and Zhang, Xu and Wang, Wei},
title = {DiGraphHal-Bench: Evaluating Multimodal Large Language Models on Complex Directed Graphs},
booktitle = {Proceedings ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Fan_DiGraphHal-Bench_Evaluating_Multimodal_Large_Language_Models_on_Complex_Directed_Graphs_CVPR_2026_paper.pdf |
Diffusion-Based sRGB Real Noise Generation via Prompt-Driven Noise Representation Learning | Jaekyun Ko, Dongjin Kim, Soomin Lee, Guanghui Wang, Tae Hyun Kim | Denoising in the sRGB image space is challenging due to large noise variability. Although end-to-end methods perform well, their effectiveness in real-world scenarios is limited by the scarcity of real noisy-clean image pairs, which are expensive and difficult to collect. To address this limitation, several generative ... | 2026/pdf/Ko_Diffusion-Based_sRGB_Real_Noise_Generation_via_Prompt-Driven_Noise_Representation_Learning_CVPR_2026_paper.pdf | @InProceedings{Ko_2026_CVPR,
author = {Ko, Jaekyun and Kim, Dongjin and Lee, Soomin and Wang, Guanghui and Kim, Tae Hyun},
title = {Diffusion-Based sRGB Real Noise Generation via Prompt-Driven Noise Representation Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and P... | https://openaccess.thecvf.com/content/CVPR2026/papers/Ko_Diffusion-Based_sRGB_Real_Noise_Generation_via_Prompt-Driven_Noise_Representation_Learning_CVPR_2026_paper.pdf |
Alert-CLIP: Abnormality-aware Latent-Enhanced Representation Tuning of CLIP for Video Anomaly Detection | Yiyan Zhu, Menghao Zhang, Haifeng Sun, Pengfei Ren, Xianao Chu, Chenye Xu, Hong Tan, Jinghan Wang, Qi Qi, Jingyu Wang | With the rise of pre-trained vision-language models such as CLIP, performing video anomaly detection (VAD) through cross-modal reasoning has become an emerging trend. However, we observe that CLIP still suffers from weak abnormality awareness: normal and abnormal descriptions are highly entangled in the text embedding ... | 2026/pdf/Zhu_Alert-CLIP_Abnormality-aware_Latent-Enhanced_Representation_Tuning_of_CLIP_for_Video_Anomaly_CVPR_2026_paper.pdf | @InProceedings{Zhu_2026_CVPR,
author = {Zhu, Yiyan and Zhang, Menghao and Sun, Haifeng and Ren, Pengfei and Chu, Xianao and Xu, Chenye and Tan, Hong and Wang, Jinghan and Qi, Qi and Wang, Jingyu},
title = {Alert-CLIP: Abnormality-aware Latent-Enhanced Representation Tuning of CLIP for Video Anomaly Detec... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhu_Alert-CLIP_Abnormality-aware_Latent-Enhanced_Representation_Tuning_of_CLIP_for_Video_Anomaly_CVPR_2026_paper.pdf |
MERG3R: A Divide-and-Conquer Approach to Large-Scale Neural Visual Geometry | Leo Kaixuan Cheng, Abdus Shaikh, Ruofan Liang, Zhijie Wu, Yushi Guan, Nandita Vijaykumar | Recent advancements in neural visual geometry, including transformer-based models such as VGGT and Pi3, have achieved impressive accuracy on 3D reconstruction tasks. However, their reliance on full attention makes them fundamentally limited by GPU memory capacity, preventing them from scaling to large, unordered image ... | 2026/pdf/Cheng_MERG3R_A_Divide-and-Conquer_Approach_to_Large-Scale_Neural_Visual_Geometry_CVPR_2026_paper.pdf | @InProceedings{Cheng_2026_CVPR,
author = {Cheng, Leo Kaixuan and Shaikh, Abdus and Liang, Ruofan and Wu, Zhijie and Guan, Yushi and Vijaykumar, Nandita},
title = {MERG3R: A Divide-and-Conquer Approach to Large-Scale Neural Visual Geometry},
booktitle = {Proceedings of the IEEE/CVF Conference on Compu... | https://openaccess.thecvf.com/content/CVPR2026/papers/Cheng_MERG3R_A_Divide-and-Conquer_Approach_to_Large-Scale_Neural_Visual_Geometry_CVPR_2026_paper.pdf |
Talking Together: Synthesizing Co-Located 3D Conversations from Audio | Mengyi Shan, Shouchieh Chang, Ziqian Bai, Shichen Liu, Yinda Zhang, Luchuan Song, Rohit Pandey, Sean Fanello, Zeng Huang | We tackle the challenging task of generating complete 3D facial animations for two interacting, co-located participants from a mixed audio stream. While existing methods often produce disembodied "talking heads" akin to a video conference call, our work is the first to explicitly model the dynamic 3D spatial relationsh... | 2026/pdf/Shan_Talking_Together_Synthesizing_Co-Located_3D_Conversations_from_Audio_CVPR_2026_paper.pdf | @InProceedings{Shan_2026_CVPR,
author = {Shan, Mengyi and Chang, Shouchieh and Bai, Ziqian and Liu, Shichen and Zhang, Yinda and Song, Luchuan and Pandey, Rohit and Fanello, Sean and Huang, Zeng},
title = {Talking Together: Synthesizing Co-Located 3D Conversations from Audio},
booktitle = {Proceeding... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shan_Talking_Together_Synthesizing_Co-Located_3D_Conversations_from_Audio_CVPR_2026_paper.pdf |
Dropping Anchor and Spherical Harmonics for Sparse-view Gaussian Splatting | Shuangkang Fang, I-Chao Shen, Xuanyang Zhang, Zesheng Wang, Yufeng Wang, Wenrui Ding, Gang YU, Takeo Igarashi | Recent 3D Gaussian Splatting (3DGS) dropout methods address overfitting under sparse-view conditions by randomly nullifying Gaussian opacities. However, we identify a neighbor compensation effect in these approaches: dropped Gaussians are often compensated by their neighbors, weakening the intended regularization. More... | 2026/pdf/Fang_Dropping_Anchor_and_Spherical_Harmonics_for_Sparse-view_Gaussian_Splatting_CVPR_2026_paper.pdf | @InProceedings{Fang_2026_CVPR,
author = {Fang, Shuangkang and Shen, I-Chao and Zhang, Xuanyang and Wang, Zesheng and Wang, Yufeng and Ding, Wenrui and YU, Gang and Igarashi, Takeo},
title = {Dropping Anchor and Spherical Harmonics for Sparse-view Gaussian Splatting},
booktitle = {Proceedings of the I... | https://openaccess.thecvf.com/content/CVPR2026/papers/Fang_Dropping_Anchor_and_Spherical_Harmonics_for_Sparse-view_Gaussian_Splatting_CVPR_2026_paper.pdf |
Neural-Centric Video Processing Pipeline for Unified Multi-Task Inference | Seyeon Lee, Juncheol Ye, Jaehong Kim, Dongsu Han | Videos are increasingly used as inputs to machine learning systems, where repeated decoding and processing across diverse downstream tasks dominate computational cost. However, existing video pipelines remain inefficient. Traditional codecs such as H.264 and H.265 are optimized for human perception and require full pix... | 2026/pdf/Lee_Neural-Centric_Video_Processing_Pipeline_for_Unified_Multi-Task_Inference_CVPR_2026_paper.pdf | @InProceedings{Lee_2026_CVPR,
author = {Lee, Seyeon and Ye, Juncheol and Kim, Jaehong and Han, Dongsu},
title = {Neural-Centric Video Processing Pipeline for Unified Multi-Task Inference},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
mont... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lee_Neural-Centric_Video_Processing_Pipeline_for_Unified_Multi-Task_Inference_CVPR_2026_paper.pdf |
MedTVT-R1: A Multimodal LLM Empowering Medical Reasoning and Diagnosis | Yuting Zhang, Kaishen Yuan, Hao Lu, Yutao Yue, Jintai Chen, Kaishun Wu | Accurate and interpretable multi-disease diagnosis remains a critical challenge in medical research, particularly when leveraging heterogeneous multimodal medical data. Current approaches often rely on single-modal data, limiting their ability to comprehensively understand complex diseases. To address this, we propose ... | 2026/pdf/Zhang_MedTVT-R1_A_Multimodal_LLM_Empowering_Medical_Reasoning_and_Diagnosis_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Yuting and Yuan, Kaishen and Lu, Hao and Yue, Yutao and Chen, Jintai and Wu, Kaishun},
title = {MedTVT-R1: A Multimodal LLM Empowering Medical Reasoning and Diagnosis},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_MedTVT-R1_A_Multimodal_LLM_Empowering_Medical_Reasoning_and_Diagnosis_CVPR_2026_paper.pdf |
MICo-150K: A Comprehensive Dataset Advancing Multi-Image Composition | Xinyu Wei, Kangrui Cen, Hongyang Wei, Zhen Guo, Bairui Li, Zeqing Wang, Jinrui Zhang, Lei Zhang | In controllable image generation, synthesizing coherent and consistent images from multiple reference inputs, i.e., **Multi-Image Composition** (MICo), remains a challenging problem, partly hindered by the lack of high-quality training data.To bridge this gap, we conduct a systematic study of MICo, categorizing it into... | 2026/pdf/Wei_MICo-150K_A_Comprehensive_Dataset_Advancing_Multi-Image_Composition_CVPR_2026_paper.pdf | @InProceedings{Wei_2026_CVPR,
author = {Wei, Xinyu and Cen, Kangrui and Wei, Hongyang and Guo, Zhen and Li, Bairui and Wang, Zeqing and Zhang, Jinrui and Zhang, Lei},
title = {MICo-150K: A Comprehensive Dataset Advancing Multi-Image Composition},
booktitle = {Proceedings of the IEEE/CVF Conference on... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wei_MICo-150K_A_Comprehensive_Dataset_Advancing_Multi-Image_Composition_CVPR_2026_paper.pdf |
Scalable Multi-View Subspace Clustering with Tensorized Anchor Guidance | Miao Jia, Xingchen Hu, Jiyuan Liu, Siwei Wang, Min Wang, Zijian Chen | Anchor-based multi-view clustering methods have gained significant attention for their effectiveness in handling large-scale datasets in recent years. The performance of these methods is highly dependent on anchor quality. However, current methods neglect the interactive relationships among cross-view anchors, failing ... | 2026/pdf/Jia_Scalable_Multi-View_Subspace_Clustering_with_Tensorized_Anchor_Guidance_CVPR_2026_paper.pdf | @InProceedings{Jia_2026_CVPR,
author = {Jia, Miao and Hu, Xingchen and Liu, Jiyuan and Wang, Siwei and Wang, Min and Chen, Zijian},
title = {Scalable Multi-View Subspace Clustering with Tensorized Anchor Guidance},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Rec... | https://openaccess.thecvf.com/content/CVPR2026/papers/Jia_Scalable_Multi-View_Subspace_Clustering_with_Tensorized_Anchor_Guidance_CVPR_2026_paper.pdf |
Good Can Sometimes be Bad: A Unified Attack against 3D Point Cloud Classifier by a Flexible Isotropic Resampling | Linkun Fan, Jiahao Zhang, Juntao Zhang, Lei Zhang, Fazhi He, Daojun Han | To ensure the robustness of 3D point cloud Deep Neural Network(3D DNN), 3D adversarial attack targeting the inference stage and backdoor attack targeting the training stage are well studied. The success of both attacks usually requires a specified permissions that attacker must have. However, the obtainable permissions... | 2026/pdf/Fan_Good_Can_Sometimes_be_Bad_A_Unified_Attack_against_3D_CVPR_2026_paper.pdf | @InProceedings{Fan_2026_CVPR,
author = {Fan, Linkun and Zhang, Jiahao and Zhang, Juntao and Zhang, Lei and He, Fazhi and Han, Daojun},
title = {Good Can Sometimes be Bad: A Unified Attack against 3D Point Cloud Classifier by a Flexible Isotropic Resampling},
booktitle = {Proceedings of the IEEE/CVF C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Fan_Good_Can_Sometimes_be_Bad_A_Unified_Attack_against_3D_CVPR_2026_paper.pdf |
CryoHype: Reconstructing a thousand cryo-EM structures with transformer-based hypernetworks | Jeffrey Gu, Minkyu Jeon, Ambri Ma, Serena Yeung-Levy, Ellen D. Zhong | Cryo-electron microscopy (cryo-EM) is an indispensable technique for determining the 3D structures of dynamic biomolecular complexes. While typically applied to image a single molecular species, cryo-EM holds great potential for structure determination of many targets simultaneously in a high-throughput fashion. Howeve... | 2026/pdf/Gu_CryoHype_Reconstructing_a_thousand_cryo-EM_structures_with_transformer-based_hypernetworks_CVPR_2026_paper.pdf | @InProceedings{Gu_2026_CVPR,
author = {Gu, Jeffrey and Jeon, Minkyu and Ma, Ambri and Yeung-Levy, Serena and Zhong, Ellen D.},
title = {CryoHype: Reconstructing a thousand cryo-EM structures with transformer-based hypernetworks},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Gu_CryoHype_Reconstructing_a_thousand_cryo-EM_structures_with_transformer-based_hypernetworks_CVPR_2026_paper.pdf |
Learning Multi-View Spatial Reasoning from Cross-View Relations | Suchae Jeong, Jaehwi Song, Haeone Lee, Hanna Kim, Jian Kim, Dongjun Lee, Dong Kyu Shin, Changyeon Kim, Dongyoon Hahm, Woogyeol Jin, Juheon Choi, Kimin Lee | Vision-language models (VLMs) have achieved impressive results on single-view vision tasks, but lack the multi-view spatial reasoning capabilities essential for embodied AI systems to understand 3D environments and manipulate objects across different viewpoints. In this work, we introduce Cross-View Relations (XVR), a ... | 2026/pdf/Jeong_Learning_Multi-View_Spatial_Reasoning_from_Cross-View_Relations_CVPR_2026_paper.pdf | @InProceedings{Jeong_2026_CVPR,
author = {Jeong, Suchae and Song, Jaehwi and Lee, Haeone and Kim, Hanna and Kim, Jian and Lee, Dongjun and Shin, Dong Kyu and Kim, Changyeon and Hahm, Dongyoon and Jin, Woogyeol and Choi, Juheon and Lee, Kimin},
title = {Learning Multi-View Spatial Reasoning from Cross-Vie... | https://openaccess.thecvf.com/content/CVPR2026/papers/Jeong_Learning_Multi-View_Spatial_Reasoning_from_Cross-View_Relations_CVPR_2026_paper.pdf |
Image-Guided Geometric Stylization of 3D Meshes | Changwoon Choi, Hyunsoo Lee, Clément Jambon, Yael Vinker, Young Min Kim | Recent generative models can create visually plausible 3D representations of objects. However, the generation process often allows for implicit control signals, such as contextual descriptions, and rarely supports bold geometric distortions beyond existing data distributions. We propose a geometric stylization framewor... | 2026/pdf/Choi_Image-Guided_Geometric_Stylization_of_3D_Meshes_CVPR_2026_paper.pdf | @InProceedings{Choi_2026_CVPR,
author = {Choi, Changwoon and Lee, Hyunsoo and Jambon, Cl\'ement and Vinker, Yael and Kim, Young Min},
title = {Image-Guided Geometric Stylization of 3D Meshes},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Choi_Image-Guided_Geometric_Stylization_of_3D_Meshes_CVPR_2026_paper.pdf |
PHANTOM: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics | Ying Shen, Jerry Xiong, Tianjiao Yu, Ismini Lourentzou | Recent advances in generative video modeling, driven by large-scale datasets and powerful architectures, have yielded remarkable visual realism. However, emerging evidence suggests that simply scaling data and model size does not endow these systems with an understanding of the underlying physical laws that govern real... | 2026/pdf/Shen_PHANTOM_Physics-Infused_Video_Generation_via_Joint_Modeling_of_Visual_and_CVPR_2026_paper.pdf | @InProceedings{Shen_2026_CVPR,
author = {Shen, Ying and Xiong, Jerry and Yu, Tianjiao and Lourentzou, Ismini},
title = {PHANTOM: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patt... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shen_PHANTOM_Physics-Infused_Video_Generation_via_Joint_Modeling_of_Visual_and_CVPR_2026_paper.pdf |
UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution | Cao Thien Tan, Phan Thi Thu Trang, Do Nghiem Duc, Ho Ngoc Anh, Hanyang Zhuang, Nguyen Duc Dung | Hybrid CNN-Transformer architectures achieve strong results in image super-resolution, but scaling attention windows or convolution kernels significantly increases computational cost, limiting deployment on resource-constrained devices. We present UCAN, a lightweight network that unifies convolution and attention to ex... | 2026/pdf/Tan_UCAN_Unified_Convolutional_Attention_Network_for_Expansive_Receptive_Fields_in_CVPR_2026_paper.pdf | @InProceedings{Tan_2026_CVPR,
author = {Tan, Cao Thien and Trang, Phan Thi Thu and Duc, Do Nghiem and Anh, Ho Ngoc and Zhuang, Hanyang and Dung, Nguyen Duc},
title = {UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution},
booktitle = {Proceeding... | https://openaccess.thecvf.com/content/CVPR2026/papers/Tan_UCAN_Unified_Convolutional_Attention_Network_for_Expansive_Receptive_Fields_in_CVPR_2026_paper.pdf |
Splat-Based Metal Artifact Reduction in Cone-Beam CT via Compact Attenuation Modeling | Kiseok Choi, Jaemin Cho, Inchul Kim, Min H. Kim | X-ray computed tomography (CT) suffers from severe metal artifacts when high-attenuation objects such as dental fillings or orthopedic implants are present. These artifacts originate from the polychromatic nature of X-rays, where attenuation varies strongly with photon energy and material composition, breaking the mono... | 2026/pdf/Choi_Splat-Based_Metal_Artifact_Reduction_in_Cone-Beam_CT_via_Compact_Attenuation_CVPR_2026_paper.pdf | @InProceedings{Choi_2026_CVPR,
author = {Choi, Kiseok and Cho, Jaemin and Kim, Inchul and Kim, Min H.},
title = {Splat-Based Metal Artifact Reduction in Cone-Beam CT via Compact Attenuation Modeling},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR... | https://openaccess.thecvf.com/content/CVPR2026/papers/Choi_Splat-Based_Metal_Artifact_Reduction_in_Cone-Beam_CT_via_Compact_Attenuation_CVPR_2026_paper.pdf |
Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality | Zekai Luo, Zongze Du, Zhouhang Zhu, Hao Zhong, Muzhi Zhu, Wen Wang, Yuling Xi, Chenchen Jing, Hao Chen, Chunhua Shen | Video face swapping is crucial in film and entertainment production, where achieving high fidelity and temporal consistency over long and complex video sequences remains a significant challenge. Inspired by recent advances in reference-guided image editing, we explore whether rich visual attributes from source videos c... | 2026/pdf/Luo_Preserving_Source_Video_Realism_High-Fidelity_Face_Swapping_for_Cinematic_Quality_CVPR_2026_paper.pdf | @InProceedings{Luo_2026_CVPR,
author = {Luo, Zekai and Du, Zongze and Zhu, Zhouhang and Zhong, Hao and Zhu, Muzhi and Wang, Wen and Xi, Yuling and Jing, Chenchen and Chen, Hao and Shen, Chunhua},
title = {Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality},
booktitle =... | https://openaccess.thecvf.com/content/CVPR2026/papers/Luo_Preserving_Source_Video_Realism_High-Fidelity_Face_Swapping_for_Cinematic_Quality_CVPR_2026_paper.pdf |
Measuring the (Un)Faithfulness of Concept-Based Explanations | Shubham Kumar, Narendra Ahuja | Deep vision models perform input-output computations that are hard to interpret. Concept-based explanation methods (CBEMs) increase interpretability by re-expressing parts of the model with human-understandable semantic units, or concepts. Checking if the derived explanations are faithful--that is, they represent the m... | 2026/pdf/Kumar_Measuring_the_UnFaithfulness_of_Concept-Based_Explanations_CVPR_2026_paper.pdf | @InProceedings{Kumar_2026_CVPR,
author = {Kumar, Shubham and Ahuja, Narendra},
title = {Measuring the (Un)Faithfulness of Concept-Based Explanations},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2026}... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kumar_Measuring_the_UnFaithfulness_of_Concept-Based_Explanations_CVPR_2026_paper.pdf |
TRANSPORTER: Transferring Visual Semantics from VLM Manifolds | Alexandros Stergiou | How do video understanding models acquire their answers? Although current Vision Language Models (VLMs) reason over complex scenes with diverse objects, action performances, and scene dynamics, understanding and controlling their internal processes remains an open challenge. Motivated by recent advancements in text-to-... | 2026/pdf/Stergiou_TRANSPORTER_Transferring_Visual_Semantics_from_VLM_Manifolds_CVPR_2026_paper.pdf | @InProceedings{Stergiou_2026_CVPR,
author = {Stergiou, Alexandros},
title = {TRANSPORTER: Transferring Visual Semantics from VLM Manifolds},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2026},
page... | https://openaccess.thecvf.com/content/CVPR2026/papers/Stergiou_TRANSPORTER_Transferring_Visual_Semantics_from_VLM_Manifolds_CVPR_2026_paper.pdf |
BALM: A Model-Agnostic Framework for Balanced Multimodal Learning under Imbalanced Missing Rates | Phuong-Anh Nguyen, Tien Anh Pham, Duc-Trong Le, Cam-Van Thi Nguyen | Learning from multiple modalities often suffers from imbalance, where information-rich modalities dominate optimization while weaker or partially missing modalities contribute less. This imbalance becomes severe in realistic settings with imbalanced missing modalities (IMR), where each modality is absent with different... | 2026/pdf/Nguyen_BALM_A_Model-Agnostic_Framework_for_Balanced_Multimodal_Learning_under_Imbalanced_CVPR_2026_paper.pdf | @InProceedings{Nguyen_2026_CVPR,
author = {Nguyen, Phuong-Anh and Pham, Tien Anh and Le, Duc-Trong and Nguyen, Cam-Van Thi},
title = {BALM: A Model-Agnostic Framework for Balanced Multimodal Learning under Imbalanced Missing Rates},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Visi... | https://openaccess.thecvf.com/content/CVPR2026/papers/Nguyen_BALM_A_Model-Agnostic_Framework_for_Balanced_Multimodal_Learning_under_Imbalanced_CVPR_2026_paper.pdf |
PerformRecast: Expression and Head Pose Disentanglement for Portrait Video Editing | Jiadong Liang, Bojun Xiong, Jie Tian, Hua Li, Xiao Long, Yong Zheng, Huan Fu | This paper primarily investigates the task of expression-only portrait video performance editing based on a driving video, which plays a crucial role in animation and film industries. Most existing research mainly focuses on portrait animation, which aims to animate a static portrait image according to the facial motio... | 2026/pdf/Liang_PerformRecast_Expression_and_Head_Pose_Disentanglement_for_Portrait_Video_Editing_CVPR_2026_paper.pdf | @InProceedings{Liang_2026_CVPR,
author = {Liang, Jiadong and Xiong, Bojun and Tian, Jie and Li, Hua and Long, Xiao and Zheng, Yong and Fu, Huan},
title = {PerformRecast: Expression and Head Pose Disentanglement for Portrait Video Editing},
booktitle = {Proceedings of the IEEE/CVF Conference on Comput... | https://openaccess.thecvf.com/content/CVPR2026/papers/Liang_PerformRecast_Expression_and_Head_Pose_Disentanglement_for_Portrait_Video_Editing_CVPR_2026_paper.pdf |
4D Primitive-Mache: Glueing Primitives for Persistent 4D Scene Reconstruction | Kirill Mazur, Marwan Taher, Andrew J. Davison | We present 4DPM, a dynamic reconstruction system that receives a casual monocular RGB video as input, and outputs a complete and persistent reconstruction of the scene. In other words, we reconstruct not only the currently visible parts of the scene, but also all previously viewed parts, which enables replaying the co... | 2026/pdf/Mazur_4D_Primitive-Mache_Glueing_Primitives_for_Persistent_4D_Scene_Reconstruction_CVPR_2026_paper.pdf | @InProceedings{Mazur_2026_CVPR,
author = {Mazur, Kirill and Taher, Marwan and Davison, Andrew J.},
title = {4D Primitive-Mache: Glueing Primitives for Persistent 4D Scene Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month... | https://openaccess.thecvf.com/content/CVPR2026/papers/Mazur_4D_Primitive-Mache_Glueing_Primitives_for_Persistent_4D_Scene_Reconstruction_CVPR_2026_paper.pdf |
HandDreamer: Zero-Shot Text to 3D Hand Model Generation using Corrective Hand Shape Guidance | Green Rosh, Prateek Kukreja, Vishakha SR, Pawan Prasad B H | The emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome, offering very little customizability to the users. While recent advancements in ... | 2026/pdf/Rosh_HandDreamer_Zero-Shot_Text_to_3D_Hand_Model_Generation_using_Corrective_CVPR_2026_paper.pdf | @InProceedings{Rosh_2026_CVPR,
author = {Rosh, Green and Kukreja, Prateek and Vishakha, SR and H, Pawan Prasad B},
title = {HandDreamer: Zero-Shot Text to 3D Hand Model Generation using Corrective Hand Shape Guidance},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern... | https://openaccess.thecvf.com/content/CVPR2026/papers/Rosh_HandDreamer_Zero-Shot_Text_to_3D_Hand_Model_Generation_using_Corrective_CVPR_2026_paper.pdf |
Zero-Shot Reconstruction of Animatable 3D Avatars with Cloth Dynamics from a Single Image | Joohyun Kwon, Geonhee Sim, Gyeongsik Moon | Existing single-image 3D human avatar methods primarily rely on rigid joint transformations, limiting their ability to model realistic cloth dynamics. We present DynaAvatar, a zero-shot framework that reconstructs animatable 3D human avatars with motion-dependent cloth dynamics from a single image. Trained on large-sca... | 2026/pdf/Kwon_Zero-Shot_Reconstruction_of_Animatable_3D_Avatars_with_Cloth_Dynamics_from_CVPR_2026_paper.pdf | @InProceedings{Kwon_2026_CVPR,
author = {Kwon, Joohyun and Sim, Geonhee and Moon, Gyeongsik},
title = {Zero-Shot Reconstruction of Animatable 3D Avatars with Cloth Dynamics from a Single Image},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kwon_Zero-Shot_Reconstruction_of_Animatable_3D_Avatars_with_Cloth_Dynamics_from_CVPR_2026_paper.pdf |
Edit-aware RAW reconstruction | Abhijith Punnappurath, Luxi Zhao, Ke Zhao, Hue Nguyen, Radek Grzeszczuk, Michael S. Brown | Users frequently edit camera images post-capture to achieve their preferred photofinishing style. While editing in the RAW domain provides greater accuracy and flexibility, most edits are performed on the camera's display-referred output (e.g., 8-bit sRGB JPEG) since RAW images are rarely stored. Existing RAW reconstru... | 2026/pdf/Punnappurath_Edit-aware_RAW_reconstruction_CVPR_2026_paper.pdf | @InProceedings{Punnappurath_2026_CVPR,
author = {Punnappurath, Abhijith and Zhao, Luxi and Zhao, Ke and Nguyen, Hue and Grzeszczuk, Radek and Brown, Michael S.},
title = {Edit-aware RAW reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CV... | https://openaccess.thecvf.com/content/CVPR2026/papers/Punnappurath_Edit-aware_RAW_reconstruction_CVPR_2026_paper.pdf |
Learning Latent Proxies for Controllable Single-Image Relighting | Haoze Zheng, Zihao Wang, Xianfeng Wu, Yajing Bai, Yexin Liu, Yun Li, Xiaogang Xu, Harry Yang | Single-image relighting is highly under-constrained: small illumination changes can produce large, nonlinear variations in shading, shadows, and specularities, while geometry and materials remain unobserved. Existing diffusion-based approaches either rely on intrinsic- or G-buffer-based pipelines that require dense and... | 2026/pdf/Zheng_Learning_Latent_Proxies_for_Controllable_Single-Image_Relighting_CVPR_2026_paper.pdf | @InProceedings{Zheng_2026_CVPR,
author = {Zheng, Haoze and Wang, Zihao and Wu, Xianfeng and Bai, Yajing and Liu, Yexin and Li, Yun and Xu, Xiaogang and Yang, Harry},
title = {Learning Latent Proxies for Controllable Single-Image Relighting},
booktitle = {Proceedings of the IEEE/CVF Conference on Comp... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zheng_Learning_Latent_Proxies_for_Controllable_Single-Image_Relighting_CVPR_2026_paper.pdf |
View-Aware Semantic Alignment for Aerial-Ground Person Re-Identification | Quan Zhang, Zeqiang Cai, Peiming Zhao, Jingze Wu, Cailun Wu, Hongbo Chen, Jianhuang Lai | Aerial-Ground Person Re-Identification (AGPReID) remains highly challenging due to drastic viewpoint variations between drones and fixed cameras. Existing methods typically follow a view-invariant paradigm, aligning shared features across views to achieve robustness. However, view-invariant inherently enforces part-lev... | 2026/pdf/Zhang_View-Aware_Semantic_Alignment_for_Aerial-Ground_Person_Re-Identification_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Quan and Cai, Zeqiang and Zhao, Peiming and Wu, Jingze and Wu, Cailun and Chen, Hongbo and Lai, Jianhuang},
title = {View-Aware Semantic Alignment for Aerial-Ground Person Re-Identification},
booktitle = {Proceedings of the IEEE/CVF Conference on Compu... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_View-Aware_Semantic_Alignment_for_Aerial-Ground_Person_Re-Identification_CVPR_2026_paper.pdf |
PhysGM: Large Physical Gaussian Model for Feed-Forward 4D Synthesis | Chunji Lv, Zequn Chen, Donglin Di, Weinan Zhang, Hao Li, Chen Wei, Yinjie Lei, Changsheng Li | Despite advances in physics-based 3D motion synthesis, current methods face key limitations: reliance on pre-reconstructed 3D Gaussian Splatting (3DGS) built from dense multi-view images with time-consuming per-scene optimization; physics integration via either inflexible, hand-specified attributes or unstable, optimiz... | 2026/pdf/Lv_PhysGM_Large_Physical_Gaussian_Model_for_Feed-Forward_4D_Synthesis_CVPR_2026_paper.pdf | @InProceedings{Lv_2026_CVPR,
author = {Lv, Chunji and Chen, Zequn and Di, Donglin and Zhang, Weinan and Li, Hao and Wei, Chen and Lei, Yinjie and Li, Changsheng},
title = {PhysGM: Large Physical Gaussian Model for Feed-Forward 4D Synthesis},
booktitle = {Proceedings of the IEEE/CVF Conference on Comp... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lv_PhysGM_Large_Physical_Gaussian_Model_for_Feed-Forward_4D_Synthesis_CVPR_2026_paper.pdf |
ChangeBridge: Spatiotemporal Image Generation with Multimodal Controls for Remote Senisng | Zhenghui Zhao, Chen Wu, Xiangyong Cao, Di Wang, Hongruixuan Chen, Datao Tang, Liangpei Zhang, Zhuo Zheng | Spatiotemporal image generation is a highly meaningful task, which can generate future scenes conditioned on given observations. However, existing change generation methods can only handle event-driven changes (e.g., new buildings) and fail to model cross-temporal variations (e.g., seasonal shifts). In this work, we pr... | 2026/pdf/Zhao_ChangeBridge_Spatiotemporal_Image_Generation_with_Multimodal_Controls_for_Remote_Senisng_CVPR_2026_paper.pdf | @InProceedings{Zhao_2026_CVPR,
author = {Zhao, Zhenghui and Wu, Chen and Cao, Xiangyong and Wang, Di and Chen, Hongruixuan and Tang, Datao and Zhang, Liangpei and Zheng, Zhuo},
title = {ChangeBridge: Spatiotemporal Image Generation with Multimodal Controls for Remote Senisng},
booktitle = {Proceeding... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhao_ChangeBridge_Spatiotemporal_Image_Generation_with_Multimodal_Controls_for_Remote_Senisng_CVPR_2026_paper.pdf |
AcTTA: Rethinking Test-Time Adaptation via Dynamic Activation | Hyeongyu Kim, Geonhui Han, Dosik Hwang | Test-time adaptation (TTA) aims to mitigate performance degradation under distribution shifts by updating model parameters during inference. Existing approaches have primarily framed adaptation around affine modulation, focusing on recalibrating normalization layers. This perspective, while effective, overlooks another... | 2026/pdf/Kim_AcTTA_Rethinking_Test-Time_Adaptation_via_Dynamic_Activation_CVPR_2026_paper.pdf | @InProceedings{Kim_2026_CVPR,
author = {Kim, Hyeongyu and Han, Geonhui and Hwang, Dosik},
title = {AcTTA: Rethinking Test-Time Adaptation via Dynamic Activation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kim_AcTTA_Rethinking_Test-Time_Adaptation_via_Dynamic_Activation_CVPR_2026_paper.pdf |
EmoStyle: Emotion-Driven Image Stylization | Jingyuan Yang, Zihuan Bai, Hui Huang | Art has long been a profound medium for expressing emotions.While existing image stylization methods effectively transform visual appearance, they often overlook the emotional impact carried by styles.To bridge this gap, we introduce Affective Image Stylization (AIS), a task that applies artistic styles to evoke specif... | 2026/pdf/Yang_EmoStyle_Emotion-Driven_Image_Stylization_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Jingyuan and Bai, Zihuan and Huang, Hui},
title = {EmoStyle: Emotion-Driven Image Stylization},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2026},
pa... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_EmoStyle_Emotion-Driven_Image_Stylization_CVPR_2026_paper.pdf |
Self-guided Semantic Inspection for Zero-Shot Composed Image Retrieval | Jingjing Zhang, Lei Zhang, Zheren Fu, Bo Hu, Zhendong Mao | Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve target images using a composed query of a reference image and a textual modification, without relying on triplet-based supervision. As the two inputs describe related but semantically unaligned information, the key challenge lies in interpreting their cross-m... | 2026/pdf/Zhang_Self-guided_Semantic_Inspection_for_Zero-Shot_Composed_Image_Retrieval_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Jingjing and Zhang, Lei and Fu, Zheren and Hu, Bo and Mao, Zhendong},
title = {Self-guided Semantic Inspection for Zero-Shot Composed Image Retrieval},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_Self-guided_Semantic_Inspection_for_Zero-Shot_Composed_Image_Retrieval_CVPR_2026_paper.pdf |
High-Fidelity Virtual Try-On beyond Paired Data Scarcity via Diffusion-based Cycle-Consistent Learning | Jia Wu, Yijing Dai, Tingfeng Cao, Meiling Wu, Tao Luo, Jian Dong Zhang, Guangming Lu, Xiaoyi Zeng | Diffusion-based virtual try-on methods rely on vast high-quality garment-person pairs, which are scarce in practice due to the high cost of data collection and preprocessing, limiting their performance in real-world scenarios.To overcome this bottleneck, we propose Cycle-Consistent Virtual Try-On (CCVTON), a diffusion-... | 2026/pdf/Wu_High-Fidelity_Virtual_Try-On_beyond_Paired_Data_Scarcity_via_Diffusion-based_Cycle-Consistent_CVPR_2026_paper.pdf | @InProceedings{Wu_2026_CVPR,
author = {Wu, Jia and Dai, Yijing and Cao, Tingfeng and Wu, Meiling and Luo, Tao and Zhang, Jian Dong and Lu, Guangming and Zeng, Xiaoyi},
title = {High-Fidelity Virtual Try-On beyond Paired Data Scarcity via Diffusion-based Cycle-Consistent Learning},
booktitle = {Procee... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wu_High-Fidelity_Virtual_Try-On_beyond_Paired_Data_Scarcity_via_Diffusion-based_Cycle-Consistent_CVPR_2026_paper.pdf |
STARFlow-V: End-to-End Video Generative Modeling with Autoregressive Normalizing Flows | Jiatao Gu, Ying Shen, Tianrong Chen, Laurent Dinh, Yuyang Wang, Miguel Angel Bautista, David Berthelot, Josh Susskind, Shuangfei Zhai | Normalizing flows (NFs) are end-to-end likelihood-based generative models for continuous data, and have recently regained attention with encouraging progress on image generation. Yet in the video generation domain, where spatiotemporal complexity and computational cost are substantially higher, state-of-the-art systems... | 2026/pdf/Gu_STARFlow-V_End-to-End_Video_Generative_Modeling_with_Autoregressive_Normalizing_Flows_CVPR_2026_paper.pdf | @InProceedings{Gu_2026_CVPR,
author = {Gu, Jiatao and Shen, Ying and Chen, Tianrong and Dinh, Laurent and Wang, Yuyang and Bautista, Miguel Angel and Berthelot, David and Susskind, Josh and Zhai, Shuangfei},
title = {STARFlow-V: End-to-End Video Generative Modeling with Autoregressive Normalizing Flows},... | https://openaccess.thecvf.com/content/CVPR2026/papers/Gu_STARFlow-V_End-to-End_Video_Generative_Modeling_with_Autoregressive_Normalizing_Flows_CVPR_2026_paper.pdf |
Vision-Language Attribute Disentanglement and Reinforcement for Lifelong Person Re-Identification | Kunlun Xu, Haotong Cheng, Jiangmeng Li, Xu Zou, Jiahuan Zhou | Lifelong person re-identification (LReID) aims to learn from varying domains to obtain a unified person retrieval model. Existing LReID approaches typically focus on learning from scratch or a visual classification-pretrained model, while the Vision-Language Model (VLM) has shown generalizable knowledge in a variety of... | 2026/pdf/Xu_Vision-Language_Attribute_Disentanglement_and_Reinforcement_for_Lifelong_Person_Re-Identification_CVPR_2026_paper.pdf | @InProceedings{Xu_2026_CVPR,
author = {Xu, Kunlun and Cheng, Haotong and Li, Jiangmeng and Zou, Xu and Zhou, Jiahuan},
title = {Vision-Language Attribute Disentanglement and Reinforcement for Lifelong Person Re-Identification},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision an... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xu_Vision-Language_Attribute_Disentanglement_and_Reinforcement_for_Lifelong_Person_Re-Identification_CVPR_2026_paper.pdf |
Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single Measurement | Lixuan Chen, Zhongnan Liu, Jesse Hamilton, James M. Balter, Jeong Joon Park, Liyue Shen | Prospective reconstruction is crucial in many clinical applications such as MRI-guided radiotherapy, which demands accurate image reconstruction and fast motion estimation from currently acquired measurements. However, prospective reconstruction remains challenging due to ultra-sparse sampling and stringent latency req... | 2026/pdf/Chen_Prospective_Dynamic_3D_MRI_Reconstruction_via_Latent-Space_Motion_Tracking_from_CVPR_2026_paper.pdf | @InProceedings{Chen_2026_CVPR,
author = {Chen, Lixuan and Liu, Zhongnan and Hamilton, Jesse and Balter, James M. and Park, Jeong Joon and Shen, Liyue},
title = {Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single Measurement},
booktitle = {Proceedings of the IEEE/CV... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chen_Prospective_Dynamic_3D_MRI_Reconstruction_via_Latent-Space_Motion_Tracking_from_CVPR_2026_paper.pdf |
Enhancing Continual Learning of Vision-Language Models via Dynamic Prefix Weighting | Hyeonseo Jang, Hyuk Kwon, Kibok Lee | We investigate recently introduced domain-class incremental learning scenarios for vision-language models (VLMs). Recent works address this challenge using parameter-efficient methods, such as prefix-tuning or adapters, which facilitate model adaptation to downstream tasks by incorporating task-specific information int... | 2026/pdf/Jang_Enhancing_Continual_Learning_of_Vision-Language_Models_via_Dynamic_Prefix_Weighting_CVPR_2026_paper.pdf | @InProceedings{Jang_2026_CVPR,
author = {Jang, Hyeonseo and Kwon, Hyuk and Lee, Kibok},
title = {Enhancing Continual Learning of Vision-Language Models via Dynamic Prefix Weighting},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Jang_Enhancing_Continual_Learning_of_Vision-Language_Models_via_Dynamic_Prefix_Weighting_CVPR_2026_paper.pdf |
Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging | Zhilin Zhu, Yabin Wang, Zhiheng Ma, Yaguang Song, Yaowei Wang, Xiaopeng Hong | Continual Test-Time Adaptation (CTTA) aims to empower perception systems to handle dynamic distribution shifts encountered after deployment. Existing methods predominantly follow a backward-alignment paradigm, which rigidly aligns incoming data with supervisory surrogates derived from the source domain. Consequently, t... | 2026/pdf/Zhu_Dance_Across_Shifts_Forward-Facilitation_Continual_Test-Time_Adaptation_through_Dynamic_Style_CVPR_2026_paper.pdf | @InProceedings{Zhu_2026_CVPR,
author = {Zhu, Zhilin and Wang, Yabin and Ma, Zhiheng and Song, Yaguang and Wang, Yaowei and Hong, Xiaopeng},
title = {Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging},
booktitle = {Proceedings of the IEEE/CVF Confe... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhu_Dance_Across_Shifts_Forward-Facilitation_Continual_Test-Time_Adaptation_through_Dynamic_Style_CVPR_2026_paper.pdf |
SAGA: Source Attribution of Generative AI Videos | Rohit Kundu, Vishal Mohanty, Hao Xiong, Shan Jia, Athula Balachandran, Amit K. Roy-Chowdhury | The proliferation of generative AI has led to hyper-realistic synthetic videos, escalating misuse risks and outstripping binary real/fake detectors. We introduce \texttt SAGA (\underline S ource \underline A ttribution of \underline G enerative \underline A I videos), the first comprehensive framework to address the u... | 2026/pdf/Kundu_SAGA_Source_Attribution_of_Generative_AI_Videos_CVPR_2026_paper.pdf | @InProceedings{Kundu_2026_CVPR,
author = {Kundu, Rohit and Mohanty, Vishal and Xiong, Hao and Jia, Shan and Balachandran, Athula and Roy-Chowdhury, Amit K.},
title = {SAGA: Source Attribution of Generative AI Videos},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kundu_SAGA_Source_Attribution_of_Generative_AI_Videos_CVPR_2026_paper.pdf |
PixARMesh: Autoregressive Mesh-Native Single-View Scene Reconstruction | Xiang Zhang, Sohyun Yoo, Hongrui Wu, Chuan Li, Jianwen Xie, Zhuowen Tu | We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed distance fields and post-hoc layout optimization, PixARMesh jointly predicts object layout and geometry within a unified model, producing c... | 2026/pdf/Zhang_PixARMesh_Autoregressive_Mesh-Native_Single-View_Scene_Reconstruction_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Xiang and Yoo, Sohyun and Wu, Hongrui and Li, Chuan and Xie, Jianwen and Tu, Zhuowen},
title = {PixARMesh: Autoregressive Mesh-Native Single-View Scene Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_PixARMesh_Autoregressive_Mesh-Native_Single-View_Scene_Reconstruction_CVPR_2026_paper.pdf |
Temporal Inversion for Learning Interval Change in Chest X-Rays | Hanbin Ko, Kyeongmin Jeon, Doowoong Choi, Chang Min Park | Recent advances in vision-language pretraining have enabled strong medical foundation models, yet most analyze radiographs in isolation, overlooking the key clinical task of comparing prior and current images to assess interval change. For chest radiographs (CXRs), capturing interval change is essential, as radiologist... | 2026/pdf/Ko_Temporal_Inversion_for_Learning_Interval_Change_in_Chest_X-Rays_CVPR_2026_paper.pdf | @InProceedings{Ko_2026_CVPR,
author = {Ko, Hanbin and Jeon, Kyeongmin and Choi, Doowoong and Park, Chang Min},
title = {Temporal Inversion for Learning Interval Change in Chest X-Rays},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Ko_Temporal_Inversion_for_Learning_Interval_Change_in_Chest_X-Rays_CVPR_2026_paper.pdf |
SelfHVD: Self-Supervised Handheld Video Deblurring | Honglei Xu, Zhilu Zhang, Junjie Fan, Xiaohe Wu, Wangmeng Zuo | Shooting video with handheld shooting devices often results in blurry frames due to shaking hands and other instability factors. Although previous video deblurring methods have achieved impressive progress, they still struggle to perform satisfactorily on real-world handheld video due to the blur domain gap between tra... | 2026/pdf/Xu_SelfHVD_Self-Supervised_Handheld_Video_Deblurring_CVPR_2026_paper.pdf | @InProceedings{Xu_2026_CVPR,
author = {Xu, Honglei and Zhang, Zhilu and Fan, Junjie and Wu, Xiaohe and Zuo, Wangmeng},
title = {SelfHVD: Self-Supervised Handheld Video Deblurring},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xu_SelfHVD_Self-Supervised_Handheld_Video_Deblurring_CVPR_2026_paper.pdf |
ARES: Unifying Asymmetric RGB-Event Stereo for Probabilistic Scene Flow Estimation | Jie Long Lee, Gim Hee Lee | Estimating dense three dimensional motion in dynamic high speed scenes remains challenging due to motion blur, illumination variation, and the limited temporal resolution of conventional cameras. We introduce ARES, a unified framework for Asymmetric RGB-Event Stereo that addresses these issues through a hybrid setup wh... | 2026/pdf/Lee_ARES_Unifying_Asymmetric_RGB-Event_Stereo_for_Probabilistic_Scene_Flow_Estimation_CVPR_2026_paper.pdf | @InProceedings{Lee_2026_CVPR,
author = {Lee, Jie Long and Lee, Gim Hee},
title = {ARES: Unifying Asymmetric RGB-Event Stereo for Probabilistic Scene Flow Estimation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
ye... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lee_ARES_Unifying_Asymmetric_RGB-Event_Stereo_for_Probabilistic_Scene_Flow_Estimation_CVPR_2026_paper.pdf |
RFDM: Residual Flow Diffusion Models for Video Editing | Mohammadreza Salehi, Mehdi Noroozi, Luca Morreale, Ruchika Chavhan, Malcolm Chadwick, Alberto Gil Couto Pimentel Ramos, Abhinav Mehrotra | Instructional video editing applies edits to an input video using only text prompts, enabling intuitive natural-language control. Despite the rapid progress, most methods still require fixed-length inputs and substantial compute. Meanwhile, autoregressive video generation enables efficient variable-length synthesis, ye... | 2026/pdf/Salehi_RFDM_Residual_Flow_Diffusion_Models_for_Video_Editing_CVPR_2026_paper.pdf | @InProceedings{Salehi_2026_CVPR,
author = {Salehi, Mohammadreza and Noroozi, Mehdi and Morreale, Luca and Chavhan, Ruchika and Chadwick, Malcolm and Gil Couto Pimentel Ramos, Alberto and Mehrotra, Abhinav},
title = {RFDM: Residual Flow Diffusion Models for Video Editing},
booktitle = {Proceedings of ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Salehi_RFDM_Residual_Flow_Diffusion_Models_for_Video_Editing_CVPR_2026_paper.pdf |
PS-SR: Pseudo-Single-Step Video Super-Resolution via Speculative Diffusion | Aiqiu Wu, Zhaofan Qiu, Ting Yao, Tao Mei | Video Super-Resolution (VSR) fundamentally struggles with a critical trade-off: single-step models offer unmatched efficiency but often lack the high-frequency detail, creativity, and visual quality of their multi-step diffusion counterparts, which are computationally prohibitive for practical use. In this paper, we pr... | 2026/pdf/Wu_PS-SR_Pseudo-Single-Step_Video_Super-Resolution_via_Speculative_Diffusion_CVPR_2026_paper.pdf | @InProceedings{Wu_2026_CVPR,
author = {Wu, Aiqiu and Qiu, Zhaofan and Yao, Ting and Mei, Tao},
title = {PS-SR: Pseudo-Single-Step Video Super-Resolution via Speculative Diffusion},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wu_PS-SR_Pseudo-Single-Step_Video_Super-Resolution_via_Speculative_Diffusion_CVPR_2026_paper.pdf |
The Power of Decaying Steps: Enhancing Attack Stability and Transferability for Sign-based Optimizers | Wei Tao, Yang Dai, Jincai Huang, Qing Tao | Crafting adversarial examples can be formulated as an optimization problem. While sign-based optimizers such as I-FGSM and MI-FGSM have become the de facto standard for the induced optimization problems, there still exist several unsolved problems in theoretical grounding and practical reliability especially in non-con... | 2026/pdf/Tao_The_Power_of_Decaying_Steps_Enhancing_Attack_Stability_and_Transferability_CVPR_2026_paper.pdf | @InProceedings{Tao_2026_CVPR,
author = {Tao, Wei and Dai, Yang and Huang, Jincai and Tao, Qing},
title = {The Power of Decaying Steps: Enhancing Attack Stability and Transferability for Sign-based Optimizers},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognit... | https://openaccess.thecvf.com/content/CVPR2026/papers/Tao_The_Power_of_Decaying_Steps_Enhancing_Attack_Stability_and_Transferability_CVPR_2026_paper.pdf |
Multi-Scale Gradient-Guided Unrolling Architecture with Adaptive Mamba for Compressive Sensing | Le Yang, Hongping Gan | In the field of Compressive Sensing (CS), deep unrolling networks (DUNs) have demonstrated exceptional performance and interpretability by integrating traditional optimization solvers with deep networks. However, existing DUNs suffer from homogenization in cross-stage feature extraction and insufficient integration of ... | 2026/pdf/Yang_Multi-Scale_Gradient-Guided_Unrolling_Architecture_with_Adaptive_Mamba_for_Compressive_Sensing_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Le and Gan, Hongping},
title = {Multi-Scale Gradient-Guided Unrolling Architecture with Adaptive Mamba for Compressive Sensing},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_Multi-Scale_Gradient-Guided_Unrolling_Architecture_with_Adaptive_Mamba_for_Compressive_Sensing_CVPR_2026_paper.pdf |
Natural Human Motion Recovery by Aligning High-Order Temporal Dynamics from Monocular Videos | Dingkun Wei, Zehong Shen, Yan Xia, Georgios Pavlakos, Yujun Shen, Xiaowei Zhou | Human motion recovered from monocular videos often appears overly smooth or dynamically inconsistent, even when joint positions are numerically accurate. We observe that this limitation stems from the absence of reliable high-order temporal cues--velocity and acceleration--which are essential for reconstructing motion ... | 2026/pdf/Wei_Natural_Human_Motion_Recovery_by_Aligning_High-Order_Temporal_Dynamics_from_CVPR_2026_paper.pdf | @InProceedings{Wei_2026_CVPR,
author = {Wei, Dingkun and Shen, Zehong and Xia, Yan and Pavlakos, Georgios and Shen, Yujun and Zhou, Xiaowei},
title = {Natural Human Motion Recovery by Aligning High-Order Temporal Dynamics from Monocular Videos},
booktitle = {Proceedings of the IEEE/CVF Conference on ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wei_Natural_Human_Motion_Recovery_by_Aligning_High-Order_Temporal_Dynamics_from_CVPR_2026_paper.pdf |
Bayesian Decomposition and Semantic Completion for Few-shot Semantic Segmentation | Guangchen Shi, Yirui Wu, Wei Zhu, Tao Wang, Hao Zhang, Bo Li, Tong Lu | Few-shot Semantic Segmentation (FSS) aims to segment objects of novel categories given only a handful of labeled examples. However, existing methods often rely on complex category-specific modeling, resulting in high computational cost and limited generalization under low-data regimes. To address these challenges, we p... | 2026/pdf/Shi_Bayesian_Decomposition_and_Semantic_Completion_for_Few-shot_Semantic_Segmentation_CVPR_2026_paper.pdf | @InProceedings{Shi_2026_CVPR,
author = {Shi, Guangchen and Wu, Yirui and Zhu, Wei and Wang, Tao and Zhang, Hao and Li, Bo and Lu, Tong},
title = {Bayesian Decomposition and Semantic Completion for Few-shot Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shi_Bayesian_Decomposition_and_Semantic_Completion_for_Few-shot_Semantic_Segmentation_CVPR_2026_paper.pdf |
OmniVGGT: Omni-Modality Driven Visual Geometry Grounded Transformer | Haosong Peng, Hao Li, Yalun Dai, Yushi Lan, Yihang Luo, Tianyu Qi, Zhengshen Zhang, Yufeng Zhan, Junfei Zhang, Wenchao Xu, Ziwei Liu | General 3D foundation models have started to lead the trend of unifying diverse vision tasks, yet most assume RGB-only inputs and ignore readily available geometric cues (e.g., camera intrinsics, poses, and depth maps). To address this issue, we introduce OmniVGGT, a novel framework that can effectively benefit from a... | 2026/pdf/Peng_OmniVGGT_Omni-Modality_Driven_Visual_Geometry_Grounded_Transformer_CVPR_2026_paper.pdf | @InProceedings{Peng_2026_CVPR,
author = {Peng, Haosong and Li, Hao and Dai, Yalun and Lan, Yushi and Luo, Yihang and Qi, Tianyu and Zhang, Zhengshen and Zhan, Yufeng and Zhang, Junfei and Xu, Wenchao and Liu, Ziwei},
title = {OmniVGGT: Omni-Modality Driven Visual Geometry Grounded Transformer},
bookt... | https://openaccess.thecvf.com/content/CVPR2026/papers/Peng_OmniVGGT_Omni-Modality_Driven_Visual_Geometry_Grounded_Transformer_CVPR_2026_paper.pdf |
Ego: Embedding-Guided Personalization of Vision-Language Models | Soroush Seifi, Simon Gardier, Vaggelis Dorovatas, Daniel Olmeda Reino, Rahaf Aljundi | AI assistants that support humans in daily life are becoming increasingly feasible, driven by the rapid advancements in multimodal language models. A key challenge lies in overcoming the generic nature of these models to deliver personalized experiences. Existing approaches to personalizing large vision language models... | 2026/pdf/Seifi_Ego_Embedding-Guided_Personalization_of_Vision-Language_Models_CVPR_2026_paper.pdf | @InProceedings{Seifi_2026_CVPR,
author = {Seifi, Soroush and Gardier, Simon and Dorovatas, Vaggelis and Reino, Daniel Olmeda and Aljundi, Rahaf},
title = {Ego: Embedding-Guided Personalization of Vision-Language Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patte... | https://openaccess.thecvf.com/content/CVPR2026/papers/Seifi_Ego_Embedding-Guided_Personalization_of_Vision-Language_Models_CVPR_2026_paper.pdf |
Think, Then Verify: A Hypothesis-Verification Multi-Agent Framework for Long Video Understanding | Zheng Wang, Haoran Chen, Haoxuan Qin, Zhipeng Wei, Tianwen Qian, Cong Bai | Long video understanding is challenging due to dense visual redundancy, long-range temporal dependencies, and the tendency of chain-of-thought and retrieval-based agents to accumulate semantic drift and correlation-driven errors. We argue that long-video reasoning should begin not with reactive retrieval, but with deli... | 2026/pdf/Wang_Think_Then_Verify_A_Hypothesis-Verification_Multi-Agent_Framework_for_Long_Video_CVPR_2026_paper.pdf | @InProceedings{Wang_2026_CVPR,
author = {Wang, Zheng and Chen, Haoran and Qin, Haoxuan and Wei, Zhipeng and Qian, Tianwen and Bai, Cong},
title = {Think, Then Verify: A Hypothesis-Verification Multi-Agent Framework for Long Video Understanding},
booktitle = {Proceedings of the IEEE/CVF Conference on ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wang_Think_Then_Verify_A_Hypothesis-Verification_Multi-Agent_Framework_for_Long_Video_CVPR_2026_paper.pdf |
HyperST: Hierarchical Hyperbolic Learning for Spatial Transcriptomics Prediction | Chen Zhang, Yilu An, Ying Chen, Hao Li, Xitong Ling, Lihao Liu, Junjun He, Yuxiang Lin, Zihui Wang, Rongshan Yu | Spatial Transcriptomics (ST) merges the benefits of pathology images and gene expression, linking molecular profiles with tissue structure to analyze spot-level function comprehensively. Predicting gene expression from histology images is a cost-effective alternative to expensive ST technologies. However, existing meth... | 2026/pdf/Zhang_HyperST_Hierarchical_Hyperbolic_Learning_for_Spatial_Transcriptomics_Prediction_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Chen and An, Yilu and Chen, Ying and Li, Hao and Ling, Xitong and Liu, Lihao and He, Junjun and Lin, Yuxiang and Wang, Zihui and Yu, Rongshan},
title = {HyperST: Hierarchical Hyperbolic Learning for Spatial Transcriptomics Prediction},
booktitle = {Pro... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_HyperST_Hierarchical_Hyperbolic_Learning_for_Spatial_Transcriptomics_Prediction_CVPR_2026_paper.pdf |
CodeDance: A Dynamic Tool-integrated MLLM for Executable Visual Reasoning | Qi Song, Honglin Li, Yingchen Yu, Haoyi Zhou, Lin Yang, Song Bai, Qi She, Zilong Huang, Yunqing Zhao | Recent releases such as o3 highlight human-like "thinking with images" reasoning that combines tool use with stepwise verification, yet most open-source approaches still rely on text-only chains, rigid visual schemas, or single-step pipelines, limiting flexibility, interpretability, and transferability on complex tasks... | 2026/pdf/Song_CodeDance_A_Dynamic_Tool-integrated_MLLM_for_Executable_Visual_Reasoning_CVPR_2026_paper.pdf | @InProceedings{Song_2026_CVPR,
author = {Song, Qi and Li, Honglin and Yu, Yingchen and Zhou, Haoyi and Yang, Lin and Bai, Song and She, Qi and Huang, Zilong and Zhao, Yunqing},
title = {CodeDance: A Dynamic Tool-integrated MLLM for Executable Visual Reasoning},
booktitle = {Proceedings of the IEEE/CV... | https://openaccess.thecvf.com/content/CVPR2026/papers/Song_CodeDance_A_Dynamic_Tool-integrated_MLLM_for_Executable_Visual_Reasoning_CVPR_2026_paper.pdf |
SpatialTree: How Spatial Intelligence Branches Out in MLLMs | Yuxi Xiao, Longfei Li, Shen Yan, Xinhang Liu, Sida Peng, Yunchao Wei, Xiaowei Zhou, Bingyi Kang | Cognitive science suggests that spatial ability develops progressively--from perception to reasoning and interaction. Yet in multimodal LLMs (MLLMs), this hierarchy remains poorly understood, as most studies focus on a narrow set of tasks. We introduce SpatialTree, a cognitive-science-inspired hierarchy that organizes ... | 2026/pdf/Xiao_SpatialTree_How_Spatial_Intelligence_Branches_Out_in_MLLMs_CVPR_2026_paper.pdf | @InProceedings{Xiao_2026_CVPR,
author = {Xiao, Yuxi and Li, Longfei and Yan, Shen and Liu, Xinhang and Peng, Sida and Wei, Yunchao and Zhou, Xiaowei and Kang, Bingyi},
title = {SpatialTree: How Spatial Intelligence Branches Out in MLLMs},
booktitle = {Proceedings of the IEEE/CVF Conference on Compute... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xiao_SpatialTree_How_Spatial_Intelligence_Branches_Out_in_MLLMs_CVPR_2026_paper.pdf |
MoVie: Broaden Your Views with Human Motion for Action Detection | Di Yang, Mahmoud Ali, Xuanlong Yu, Xi Shen, Quan Kong, Gianpiero Francesca, François Brémond | Human action detection in videos requires both semantic recognition and accurate modeling of motion. While recent video foundation models have advanced visual semantics, they still struggle to capture complex and compositional actions due to the limited representation ability of motion. Human skeleton sequences, which ... | 2026/pdf/Yang_MoVie_Broaden_Your_Views_with_Human_Motion_for_Action_Detection_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Di and Ali, Mahmoud and Yu, Xuanlong and Shen, Xi and Kong, Quan and Francesca, Gianpiero and Br\'emond, Fran\c{c}ois},
title = {MoVie: Broaden Your Views with Human Motion for Action Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Com... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_MoVie_Broaden_Your_Views_with_Human_Motion_for_Action_Detection_CVPR_2026_paper.pdf |
D^3FER: Dual Channel and Dual Branch Network for Robust Facial Expression Recognition under Dual Challenges | Hui Tang, Yifan He, Zhong Jin | Facial expression recognition (FER) in the wild is challenged by co-occurring visual perturbations (e.g., occlusions, pose variations) and label noise. Existing methods often address these issues in isolation, failing to handle their compound effects effectively. To this end, we propose D^3FER (Dual channel and Dual br... | 2026/pdf/Tang_D3FER_Dual_Channel_and_Dual_Branch_Network_for_Robust_Facial_CVPR_2026_paper.pdf | @InProceedings{Tang_2026_CVPR,
author = {Tang, Hui and He, Yifan and Jin, Zhong},
title = {D{\textasciicircum}3FER: Dual Channel and Dual Branch Network for Robust Facial Expression Recognition under Dual Challenges},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Tang_D3FER_Dual_Channel_and_Dual_Branch_Network_for_Robust_Facial_CVPR_2026_paper.pdf |
STAC: Plug-and-Play Spatio-Temporal Aware Cache Compression for Streaming 3D Reconstruction | Runze Wang, Yuxuan Song, Youcheng Cai, Ligang Liu | Online 3D reconstruction from streaming inputs requires both long-term temporal consistency and efficient memory usage. Although causal variants of VGGT address this challenge through a key-value (KV) cache mechanism, the cache grows linearly with the stream length, creating a major memory bottleneck. Under limited mem... | 2026/pdf/Wang_STAC_Plug-and-Play_Spatio-Temporal_Aware_Cache_Compression_for_Streaming_3D_Reconstruction_CVPR_2026_paper.pdf | @InProceedings{Wang_2026_CVPR,
author = {Wang, Runze and Song, Yuxuan and Cai, Youcheng and Liu, Ligang},
title = {STAC: Plug-and-Play Spatio-Temporal Aware Cache Compression for Streaming 3D Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogniti... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wang_STAC_Plug-and-Play_Spatio-Temporal_Aware_Cache_Compression_for_Streaming_3D_Reconstruction_CVPR_2026_paper.pdf |
PECCVAI: Overcoming the Brittleness of AI Image Watermarking Under Visual Paraphrasing Attacks | Shreyas Dixit, Ashhar Aziz, Shashwat Bajpai, Vasu Sharma, Aman Chadha, Vinija Jain, Amitava Das | By 2026, up to 90% of online content may be synthetically generated, raising urgent concerns about the proliferation of AI-driven disinformation. In response, policymakers and technology companies are turning to watermarking as a safeguard: California's Bill AB 321 mandates watermarking of AI-generated media, while fir... | 2026/pdf/Dixit_PECCVAI_Overcoming_the_Brittleness_of_AI_Image_Watermarking_Under_Visual_CVPR_2026_paper.pdf | @InProceedings{Dixit_2026_CVPR,
author = {Dixit, Shreyas and Aziz, Ashhar and Bajpai, Shashwat and Sharma, Vasu and Chadha, Aman and Jain, Vinija and Das, Amitava},
title = {PECCVAI: Overcoming the Brittleness of AI Image Watermarking Under Visual Paraphrasing Attacks},
booktitle = {Proceedings of th... | https://openaccess.thecvf.com/content/CVPR2026/papers/Dixit_PECCVAI_Overcoming_the_Brittleness_of_AI_Image_Watermarking_Under_Visual_CVPR_2026_paper.pdf |
Towards Robust Sequential Decomposition for Complex Image Editing | Zilai Zeng, Mingdeng Cao, Zijie Li, Xiaochen Lian, Yichun Shi, Peihao Zhu, Chen Sun, Peng Wang | Recent advances in visual generative models have enabled high-fidelity image editing guided by human instructions. However, these models often struggle with complex instructions involving combinatorial editing operations or inter-step dependencies. This difficulty stems from the limitations of two canonical paradigms: ... | 2026/pdf/Zeng_Towards_Robust_Sequential_Decomposition_for_Complex_Image_Editing_CVPR_2026_paper.pdf | @InProceedings{Zeng_2026_CVPR,
author = {Zeng, Zilai and Cao, Mingdeng and Li, Zijie and Lian, Xiaochen and Shi, Yichun and Zhu, Peihao and Sun, Chen and Wang, Peng},
title = {Towards Robust Sequential Decomposition for Complex Image Editing},
booktitle = {Proceedings of the IEEE/CVF Conference on Co... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zeng_Towards_Robust_Sequential_Decomposition_for_Complex_Image_Editing_CVPR_2026_paper.pdf |
Prototypical Action Reasoning Facilitated by Vision-Language Alignment for Egocentric Action Anticipation | Jiang Shao, Xinbo Zhao, Wenyin Tuo, Xiaochun Zou | Egocentric Action Anticipation aims to infer future actions from videos, which is crucial for embodied AI systems. However, its advancement is hindered by the inherent stochasticity of the future, which introduces significant prediction uncertainty. Prevailing methods typically adopt an end-to-end approach to model hol... | 2026/pdf/Shao_Prototypical_Action_Reasoning_Facilitated_by_Vision-Language_Alignment_for_Egocentric_Action_CVPR_2026_paper.pdf | @InProceedings{Shao_2026_CVPR,
author = {Shao, Jiang and Zhao, Xinbo and Tuo, Wenyin and Zou, Xiaochun},
title = {Prototypical Action Reasoning Facilitated by Vision-Language Alignment for Egocentric Action Anticipation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patt... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shao_Prototypical_Action_Reasoning_Facilitated_by_Vision-Language_Alignment_for_Egocentric_Action_CVPR_2026_paper.pdf |
GA-VLN: Geometry-Aware BEV Representation for Efficient Vision-Language Navigation | Jiahao Yang, Zihan Wang, Xiangyang Li, Xing Zhu, Yujun Shen, Yinghao Xu, Shuqiang Jiang | Despite significant progress in Vision-Language Navigation (VLN), existing approaches still rely on dense RGB videos that produce excessive patch tokens and lack explicit spatial structure, resulting in substantial computational overhead and limited spatial reasoning. To address these issues, we introduce the Geometry-... | 2026/pdf/Yang_GA-VLN_Geometry-Aware_BEV_Representation_for_Efficient_Vision-Language_Navigation_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Jiahao and Wang, Zihan and Li, Xiangyang and Zhu, Xing and Shen, Yujun and Xu, Yinghao and Jiang, Shuqiang},
title = {GA-VLN: Geometry-Aware BEV Representation for Efficient Vision-Language Navigation},
booktitle = {Proceedings of the IEEE/CVF Conference... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_GA-VLN_Geometry-Aware_BEV_Representation_for_Efficient_Vision-Language_Navigation_CVPR_2026_paper.pdf |
Context-Nav: Context-Driven Exploration and Viewpoint-Aware 3D Spatial Reasoning for Instance Navigation | Won Shik Jang, Ue-Hwan Kim | Text-goal instance navigation (TGIN) asks an agent to resolve a single, free-form description into actions that reach the correct object instance among same-category distractors. We present Context-Nav, which elevates long, contextual captions from a local matching cue to a global exploration prior and verifies candida... | 2026/pdf/Jang_Context-Nav_Context-Driven_Exploration_and_Viewpoint-Aware_3D_Spatial_Reasoning_for_Instance_CVPR_2026_paper.pdf | @InProceedings{Jang_2026_CVPR,
author = {Jang, Won Shik and Kim, Ue-Hwan},
title = {Context-Nav: Context-Driven Exploration and Viewpoint-Aware 3D Spatial Reasoning for Instance Navigation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
mo... | https://openaccess.thecvf.com/content/CVPR2026/papers/Jang_Context-Nav_Context-Driven_Exploration_and_Viewpoint-Aware_3D_Spatial_Reasoning_for_Instance_CVPR_2026_paper.pdf |
QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer | Zhizhen Pan, Hesong Wang, Huan Wang | Estimating 3D attributes directly from images has advanced rapidly with the Visual Geometry Grounded Transformer (VGGT), which predicts camera parameters, depth maps, and point clouds in a single forward pass. However, its 1.2B-parameter scale severely limits deployment on resource-constrained platforms such as UAVs an... | 2026/pdf/Pan_QVGGT_Post-Training_Quantized_Visual_Geometry_Grounded_Transformer_CVPR_2026_paper.pdf | @InProceedings{Pan_2026_CVPR,
author = {Pan, Zhizhen and Wang, Hesong and Wang, Huan},
title = {QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
yea... | https://openaccess.thecvf.com/content/CVPR2026/papers/Pan_QVGGT_Post-Training_Quantized_Visual_Geometry_Grounded_Transformer_CVPR_2026_paper.pdf |
OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives | Zedong Dan, Zijie Wang, Wei Zhang, Xiangru Lin, Weiming Zhang, Xiao Tan, Jingdong Wang, Liang Lin, Guanbin Li | Offline vectorized maps constitute critical infrastructure for high-precision autonomous driving and mapping services. Existing approaches rely predominantly on single ego-vehicle trajectories, which fundamentally suffer from viewpoint insufficiency: while memory-based methods extend observation time by aggregating ego... | 2026/pdf/Dan_OptiMVMap_Offline_Vectorized_Map_Construction_via_Optimal_Multi-vehicle_Perspectives_CVPR_2026_paper.pdf | @InProceedings{Dan_2026_CVPR,
author = {Dan, Zedong and Wang, Zijie and Zhang, Wei and Lin, Xiangru and Zhang, Weiming and Tan, Xiao and Wang, Jingdong and Lin, Liang and Li, Guanbin},
title = {OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives},
booktitle = {Procee... | https://openaccess.thecvf.com/content/CVPR2026/papers/Dan_OptiMVMap_Offline_Vectorized_Map_Construction_via_Optimal_Multi-vehicle_Perspectives_CVPR_2026_paper.pdf |
SAME: Sparse and Anchored Model Editing for Heterogeneous Incremental Learning under Limited Data | Zixuan Duan, Zeyu Zhang, Fengyuan Lu, Shaofeng Zhang, Wenbin Li, Qi Fan, Yang Gao | Existing Incremental Learning (IL) methods are primarily evaluated under either a single-domain class-incremental setting, or a multi-domain task-incremental setting with known task identifiers. However, these assumptions often fail to hold in real-world applications. To bridge this gap, we introduce Heterogeneous Incr... | 2026/pdf/Duan_SAME_Sparse_and_Anchored_Model_Editing_for_Heterogeneous_Incremental_Learning_CVPR_2026_paper.pdf | @InProceedings{Duan_2026_CVPR,
author = {Duan, Zixuan and Zhang, Zeyu and Lu, Fengyuan and Zhang, Shaofeng and Li, Wenbin and Fan, Qi and Gao, Yang},
title = {SAME: Sparse and Anchored Model Editing for Heterogeneous Incremental Learning under Limited Data},
booktitle = {Proceedings of the IEEE/CVF C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Duan_SAME_Sparse_and_Anchored_Model_Editing_for_Heterogeneous_Incremental_Learning_CVPR_2026_paper.pdf |
Learning Explicit Continuous Motion Representation for Dynamic Gaussian Splatting from Monocular Videos | Xuankai Zhang, Junjin Xiao, Shangwei Huang, Wei-shi Zheng, Qing Zhang | We present an approach for high-quality dynamic Gaussian Splatting from monocular videos. To this end, we in this work go one step further beyond previous methods to explicitly model continuous position and orientation deformation of dynamic Gaussians, using an SE(3) B-spline motion bases with a compact set of control ... | 2026/pdf/Zhang_Learning_Explicit_Continuous_Motion_Representation_for_Dynamic_Gaussian_Splatting_from_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Xuankai and Xiao, Junjin and Huang, Shangwei and Zheng, Wei-shi and Zhang, Qing},
title = {Learning Explicit Continuous Motion Representation for Dynamic Gaussian Splatting from Monocular Videos},
booktitle = {Proceedings of the IEEE/CVF Conference on ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_Learning_Explicit_Continuous_Motion_Representation_for_Dynamic_Gaussian_Splatting_from_CVPR_2026_paper.pdf |
MotionV2V: Editing Motion in a Video | Ryan Burgert, Charles Herrmann, Forrester Cole, Michael S Ryoo, Neal Wadhwa, Andrey Voynov, Nataniel Ruiz | While generative video models have achieved remarkable fidelity and consistency, applying these capabilities to video editing remains a complex challenge. Recent research has extensively explored motion controllability as a means to enhance text-to-video generation or image animation; however, we identify precise motio... | 2026/pdf/Burgert_MotionV2V_Editing_Motion_in_a_Video_CVPR_2026_paper.pdf | @InProceedings{Burgert_2026_CVPR,
author = {Burgert, Ryan and Herrmann, Charles and Cole, Forrester and Ryoo, Michael S and Wadhwa, Neal and Voynov, Andrey and Ruiz, Nataniel},
title = {MotionV2V: Editing Motion in a Video},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and P... | https://openaccess.thecvf.com/content/CVPR2026/papers/Burgert_MotionV2V_Editing_Motion_in_a_Video_CVPR_2026_paper.pdf |
DC-Merge: Improving Model Merging with Directional Consistency | Han-Chen Zhang, Zi-Hao Zhou, Mao-Lin Luo, Shimin Di, Min-Ling Zhang, Tong Wei | Model merging aims to integrate multiple task-adapted models into a unified model that preserves the knowledge of each task. In this paper, we identify that the key to this knowledge retention lies in maintaining the directional consistency of singular spaces between merged multi-task vector and individual task vectors... | 2026/pdf/Zhang_DC-Merge_Improving_Model_Merging_with_Directional_Consistency_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Han-Chen and Zhou, Zi-Hao and Luo, Mao-Lin and Di, Shimin and Zhang, Min-Ling and Wei, Tong},
title = {DC-Merge: Improving Model Merging with Directional Consistency},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern R... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_DC-Merge_Improving_Model_Merging_with_Directional_Consistency_CVPR_2026_paper.pdf |
Human-Centric Multi-Exposure Fusion: Benchmark and Bi-level Cognition Distillation Framework | Jingjie Shang, Tengyu Ma, Heng Zhang, Jinyuan Liu, Risheng Liu, Yuan Wang, Xiaochen Bo | Multi-Exposure Fusion (MEF) seeks to generate a single high-quality image from multiple inputs captured at different exposure levels. Despite substantial progress, most existing approaches depend on statistical metrics that poorly reflect human perceptual preferences. Electroencephalography (EEG) provides a direct phys... | 2026/pdf/Shang_Human-Centric_Multi-Exposure_Fusion_Benchmark_and_Bi-level_Cognition_Distillation_Framework_CVPR_2026_paper.pdf | @InProceedings{Shang_2026_CVPR,
author = {Shang, Jingjie and Ma, Tengyu and Zhang, Heng and Liu, Jinyuan and Liu, Risheng and Wang, Yuan and Bo, Xiaochen},
title = {Human-Centric Multi-Exposure Fusion: Benchmark and Bi-level Cognition Distillation Framework},
booktitle = {Proceedings of the IEEE/CVF ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shang_Human-Centric_Multi-Exposure_Fusion_Benchmark_and_Bi-level_Cognition_Distillation_Framework_CVPR_2026_paper.pdf |
Hierarchical Attacks for Multi-Modal Multi-Agent Reasoning | Hao Zhou, Tiru Wu, Yan Jiang, Wanqi Zhou, Junxing Hu, Ai Han | Multi-modal multi-agent systems (MM-MAS) have gained increasing attention for their capacity to enable complex reasoning and coordination across diverse modalities. As these systems continue to expand in scale and functionality, investigating their potential vulnerabilities has become increasingly important.However, ex... | 2026/pdf/Zhou_Hierarchical_Attacks_for_Multi-Modal_Multi-Agent_Reasoning_CVPR_2026_paper.pdf | @InProceedings{Zhou_2026_CVPR,
author = {Zhou, Hao and Wu, Tiru and Jiang, Yan and Zhou, Wanqi and Hu, Junxing and Han, Ai},
title = {Hierarchical Attacks for Multi-Modal Multi-Agent Reasoning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhou_Hierarchical_Attacks_for_Multi-Modal_Multi-Agent_Reasoning_CVPR_2026_paper.pdf |
When Robots Obey the Patch: Universal Transferable Patch Attacks on Vision-Language-Action Models | Hui Lu, Yi Yu, Yiming Yang, Chenyu Yi, Qixin Zhang, Bingquan Shen, Alex C. Kot, Xudong Jiang | Vision-Language-Action (VLA) models are vulnerable to adversarial attacks, yet universal and transferable attacks remain underexplored, as most existing patches overfit to a single model and fail in black-box settings. To address this gap, we present a systematic study of universal, transferable adversarial patches aga... | 2026/pdf/Lu_When_Robots_Obey_the_Patch_Universal_Transferable_Patch_Attacks_on_CVPR_2026_paper.pdf | @InProceedings{Lu_2026_CVPR,
author = {Lu, Hui and Yu, Yi and Yang, Yiming and Yi, Chenyu and Zhang, Qixin and Shen, Bingquan and Kot, Alex C. and Jiang, Xudong},
title = {When Robots Obey the Patch: Universal Transferable Patch Attacks on Vision-Language-Action Models},
booktitle = {Proceedings of t... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lu_When_Robots_Obey_the_Patch_Universal_Transferable_Patch_Attacks_on_CVPR_2026_paper.pdf |
Life-IQA: Boosting Blind Image Quality Assessment through GCN-enhanced Layer Interaction and MoE-based Feature Decoupling | Long Tang, Huiyu Duan, Guoquan Zheng, Jianbo Zhang, Jie Hao, Liang Yuan | Blind image quality assessment (BIQA) plays a crucial role in evaluating and optimizing visual experience. Most existing BIQA approaches fuse shallow and deep features extracted from backbone networks, while overlooking the unequal contributions to quality prediction. Moreover, while various vision encoder backbones ar... | 2026/pdf/Tang_Life-IQA_Boosting_Blind_Image_Quality_Assessment_through_GCN-enhanced_Layer_Interaction_CVPR_2026_paper.pdf | @InProceedings{Tang_2026_CVPR,
author = {Tang, Long and Duan, Huiyu and Zheng, Guoquan and Zhang, Jianbo and Hao, Jie and Yuan, Liang},
title = {Life-IQA: Boosting Blind Image Quality Assessment through GCN-enhanced Layer Interaction and MoE-based Feature Decoupling},
booktitle = {Proceedings of the ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Tang_Life-IQA_Boosting_Blind_Image_Quality_Assessment_through_GCN-enhanced_Layer_Interaction_CVPR_2026_paper.pdf |
Random Wins All: Rethinking Grouping Strategies for Vision Tokens | Qihang Fan, Yuang Ai, Huaibo Huang, Ran He | Since Transformers are introduced into vision architectures, their quadratic complexity has always been a significant issue that many research efforts aim to address. A representative approach involves grouping tokens, performing self-attention calculations within each group. To this end, various carefully designed gro... | 2026/pdf/Fan_Random_Wins_All_Rethinking_Grouping_Strategies_for_Vision_Tokens_CVPR_2026_paper.pdf | @InProceedings{Fan_2026_CVPR,
author = {Fan, Qihang and Ai, Yuang and Huang, Huaibo and He, Ran},
title = {Random Wins All: Rethinking Grouping Strategies for Vision Tokens},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June}... | https://openaccess.thecvf.com/content/CVPR2026/papers/Fan_Random_Wins_All_Rethinking_Grouping_Strategies_for_Vision_Tokens_CVPR_2026_paper.pdf |
Seeing through boxes: Non-Line-of-Sight 3D Reconstruction from Radar Signals | Jiachen Lu, Hailan Shanbhag, Haitham Al Hassanieh | Reconstructing object geometry from radio frequency (RF) signals is fundamentally challenging due to the lensless imaging nature of RF sensing, which leads to low spatial resolution and high noise. Unlike light signals, RF signals can penetrate occlusions and thus capture information about hidden scenes. Existing Non-L... | 2026/pdf/Lu_Seeing_through_boxes_Non-Line-of-Sight_3D_Reconstruction_from_Radar_Signals_CVPR_2026_paper.pdf | @InProceedings{Lu_2026_CVPR,
author = {Lu, Jiachen and Shanbhag, Hailan and Al Hassanieh, Haitham},
title = {Seeing through boxes: Non-Line-of-Sight 3D Reconstruction from Radar Signals},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lu_Seeing_through_boxes_Non-Line-of-Sight_3D_Reconstruction_from_Radar_Signals_CVPR_2026_paper.pdf |
R-4B: Incentivizing General-Purpose Auto-Thinking in MLLMs via Bi-Mode Annealing and Reinforce Learning | Qi Yang, Bolin Ni, Shiming Xiang, Houwen Peng | Multimodal Large Language Models (MLLMs) with explicit step-by-step reasoning have achieved strong performance on complex tasks. However, such reasoning is unnecessary for many simple queries and introduces substantial computational overhead. To address this inefficiency, we present R-4B, an auto-thinking MLLM that dyn... | 2026/pdf/Yang_R-4B_Incentivizing_General-Purpose_Auto-Thinking_in_MLLMs_via_Bi-Mode_Annealing_and_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Qi and Ni, Bolin and Xiang, Shiming and Peng, Houwen},
title = {R-4B: Incentivizing General-Purpose Auto-Thinking in MLLMs via Bi-Mode Annealing and Reinforce Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern R... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_R-4B_Incentivizing_General-Purpose_Auto-Thinking_in_MLLMs_via_Bi-Mode_Annealing_and_CVPR_2026_paper.pdf |
UniRain: Unified Image Deraining with RAG-based Dataset Distillation and Multi-objective Reweighted Optimization | Qianfeng Yang, Qiyuan Guan, Xiang Chen, Jiyu Jin, Guiyue Jin, Jiangxin Dong | Despite significant progress has been made in image deraining, we note that most existing methods are often developed for only specific types of rain degradation and fail to generalize across diverse real-world rainy scenes. How to effectively model different rain degradations within a universal framework is important ... | 2026/pdf/Yang_UniRain_Unified_Image_Deraining_with_RAG-based_Dataset_Distillation_and_Multi-objective_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Qianfeng and Guan, Qiyuan and Chen, Xiang and Jin, Jiyu and Jin, Guiyue and Dong, Jiangxin},
title = {UniRain: Unified Image Deraining with RAG-based Dataset Distillation and Multi-objective Reweighted Optimization},
booktitle = {Proceedings of the IEEE/... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_UniRain_Unified_Image_Deraining_with_RAG-based_Dataset_Distillation_and_Multi-objective_CVPR_2026_paper.pdf |
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