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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Unlocking Pre-trained Weights: Parameter Inheritance for Zero-Shot Initialization | Jiaze Xu, Shiyu Xia, Jiaqi Lv, Xin Geng | Appropriate parameter initialization is crucial for reducing the training cost of deep neural networks. Graph HyperNetworks (GHN) have emerged as a promising approach for initializing diverse architectures, with recent methods such as Task-Aware Learngene (TAL) further attempting to leverage pre-trained model knowledge... | 2026/pdf/Xu_Unlocking_Pre-trained_Weights_Parameter_Inheritance_for_Zero-Shot_Initialization_CVPR_2026_paper.pdf | @InProceedings{Xu_2026_CVPR,
author = {Xu, Jiaze and Xia, Shiyu and Lv, Jiaqi and Geng, Xin},
title = {Unlocking Pre-trained Weights: Parameter Inheritance for Zero-Shot Initialization},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xu_Unlocking_Pre-trained_Weights_Parameter_Inheritance_for_Zero-Shot_Initialization_CVPR_2026_paper.pdf |
Fast-FoundationStereo: Real-Time Zero-Shot Stereo Matching | Bowen Wen, Shaurya Dewan, Stan Birchfield | Stereo foundation models achieve strong zero-shotgeneralization but remain computationally prohibitive forreal-time applications. Efficient stereo architectures, on the other hand, sacrificerobustness for speed and require costly per-domain fine-tuning.To bridge this gap, we present Fast-FoundationStereo, a family of a... | 2026/pdf/Wen_Fast-FoundationStereo_Real-Time_Zero-Shot_Stereo_Matching_CVPR_2026_paper.pdf | @InProceedings{Wen_2026_CVPR,
author = {Wen, Bowen and Dewan, Shaurya and Birchfield, Stan},
title = {Fast-FoundationStereo: Real-Time Zero-Shot Stereo Matching},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wen_Fast-FoundationStereo_Real-Time_Zero-Shot_Stereo_Matching_CVPR_2026_paper.pdf |
UniChange: Unifying Change Detection with Multimodal Large Language Model | Xu Zhang, Danyang Li, Xiaohang Dong, Tianhao Wu, Hualong Yu, Jianye Wang, Qicheng Li, Xiang Li | Change detection (CD) is a fundamental task for monitoring and analysing land cover dynamics. While recent high performance models and high quality datasets have significantly advanced the field, a critical limitation persists. Current models typically acquire limited knowledge from single-type annotated data and canno... | 2026/pdf/Zhang_UniChange_Unifying_Change_Detection_with_Multimodal_Large_Language_Model_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Xu and Li, Danyang and Dong, Xiaohang and Wu, Tianhao and Yu, Hualong and Wang, Jianye and Li, Qicheng and Li, Xiang},
title = {UniChange: Unifying Change Detection with Multimodal Large Language Model},
booktitle = {Proceedings of the IEEE/CVF Confere... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_UniChange_Unifying_Change_Detection_with_Multimodal_Large_Language_Model_CVPR_2026_paper.pdf |
Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization | Tsai-Shien Chen, Aliaksandr Siarohin, Gordon Guocheng Qian, Kuan-Chieh Jackson Wang, Egor Nemchinov, Moayed Haji-Ali, Riza Alp Guler, Willi Menapace, Ivan Skorokhodov, Anil Kag, Jun-Yan Zhu, Sergey Tulyakov | Visual concept personalization aims to transfer only specific image attributes, such as identity, expression, lighting, and style, into unseen contexts. However, existing methods rely on holistic embeddings from general-purpose image encoders, which entangle multiple visual factors and make it difficult to isolate a si... | 2026/pdf/Chen_Omni-Attribute_Open-vocabulary_Attribute_Encoder_for_Visual_Concept_Personalization_CVPR_2026_paper.pdf | @InProceedings{Chen_2026_CVPR,
author = {Chen, Tsai-Shien and Siarohin, Aliaksandr and Qian, Gordon Guocheng and Wang, Kuan-Chieh Jackson and Nemchinov, Egor and Haji-Ali, Moayed and Guler, Riza Alp and Menapace, Willi and Skorokhodov, Ivan and Kag, Anil and Zhu, Jun-Yan and Tulyakov, Sergey},
title = {O... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chen_Omni-Attribute_Open-vocabulary_Attribute_Encoder_for_Visual_Concept_Personalization_CVPR_2026_paper.pdf |
LangField4D: Learning Identity-Adaptive and Spatio-Temporal Continuous 4D Language Fields for Dynamic Scenes | Yichao Xu, Qiaowei Miao, Jinsheng Quan, Wei Yang, Zhihui Li, Yawei Luo | Constructing a 4D language field that supports open-vocabulary queries is essential for semantic perception and interaction in dynamic environments. Existing 4D Gaussian-based approaches face two major challenges. First, the assumption of a static identity per Gaussian leads to semantic inconsistency, as motion fields ... | 2026/pdf/Xu_LangField4D_Learning_Identity-Adaptive_and_Spatio-Temporal_Continuous_4D_Language_Fields_for_CVPR_2026_paper.pdf | @InProceedings{Xu_2026_CVPR,
author = {Xu, Yichao and Miao, Qiaowei and Quan, Jinsheng and Yang, Wei and Li, Zhihui and Luo, Yawei},
title = {LangField4D: Learning Identity-Adaptive and Spatio-Temporal Continuous 4D Language Fields for Dynamic Scenes},
booktitle = {Proceedings of the IEEE/CVF Confere... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xu_LangField4D_Learning_Identity-Adaptive_and_Spatio-Temporal_Continuous_4D_Language_Fields_for_CVPR_2026_paper.pdf |
Representing 3D Faces with Learnable B-Spline Volumes | Prashanth Chandran, Daoye Wang, Timo Bolkart | We present CUBE (Control-based Unified B-Splinie Encoding), a new geometric representation for human faces that combines B-spline volumes with learned features, and demonstrate its use as a decoder for 3D scan registration and monocular 3D face reconstruction. Unlike existing B-spline representations with 3D control po... | 2026/pdf/Chandran_Representing_3D_Faces_with_Learnable_B-Spline_Volumes_CVPR_2026_paper.pdf | @InProceedings{Chandran_2026_CVPR,
author = {Chandran, Prashanth and Wang, Daoye and Bolkart, Timo},
title = {Representing 3D Faces with Learnable B-Spline Volumes},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
yea... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chandran_Representing_3D_Faces_with_Learnable_B-Spline_Volumes_CVPR_2026_paper.pdf |
ChartR: Evaluating Reasoning Accuracy and Robustness in Chart Question Answering | Xiaojun Chen, Sixiao Luo, Ziqi Liu, Min Yang, Qin Zhang, Liang-Jie Zhang | Chart Question Answering (CQA) benchmarks are critical for evaluating Multimodal Large Language Models (MLLMs) on visual data reasoning. Existing benchmarks focus mainly on final-answer correctness, ignoring intermediate reasoning steps and the propagation of errors in multi-step processes. To address this, we introduc... | 2026/pdf/Chen_ChartR_Evaluating_Reasoning_Accuracy_and_Robustness_in_Chart_Question_Answering_CVPR_2026_paper.pdf | @InProceedings{Chen_2026_CVPR,
author = {Chen, Xiaojun and Luo, Sixiao and Liu, Ziqi and Yang, Min and Zhang, Qin and Zhang, Liang-Jie},
title = {ChartR: Evaluating Reasoning Accuracy and Robustness in Chart Question Answering},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision a... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chen_ChartR_Evaluating_Reasoning_Accuracy_and_Robustness_in_Chart_Question_Answering_CVPR_2026_paper.pdf |
Elucidating the Design Space of Arbitrary-Noise-Based Diffusion Models | Xingyu Qiu, Mengying Yang, Xinghua Ma, Dong Liang, Fanding Li, Gongning Luo, Wei Wang, Kuanquan Wang, Shuo Li | Although EDM aims to unify the design space of diffusion models, its reliance on fixed Gaussian noise prevents it from explaining emerging flow-based methods that diffuse arbitrary noise. Moreover, our study reveals that EDM's forcible injection of Gaussian noise has adverse effects on image restoration task, as it cor... | 2026/pdf/Qiu_Elucidating_the_Design_Space_of_Arbitrary-Noise-Based_Diffusion_Models_CVPR_2026_paper.pdf | @InProceedings{Qiu_2026_CVPR,
author = {Qiu, Xingyu and Yang, Mengying and Ma, Xinghua and Liang, Dong and Li, Fanding and Luo, Gongning and Wang, Wei and Wang, Kuanquan and Li, Shuo},
title = {Elucidating the Design Space of Arbitrary-Noise-Based Diffusion Models},
booktitle = {Proceedings of the IE... | https://openaccess.thecvf.com/content/CVPR2026/papers/Qiu_Elucidating_the_Design_Space_of_Arbitrary-Noise-Based_Diffusion_Models_CVPR_2026_paper.pdf |
VIVA: VLM-Guided Instruction-Based Video Editing with Reward Optimization | Xiaoyan Cong, Haotian Yang, Angtian Wang, Yizhi Wang, Yiding Yang, Canyu Zhang, Chongyang Ma | Instruction-based video editing aims to modify an input video according to a natural-language instruction while preserving content fidelity and temporal coherence. However, existing diffusion-based approaches are often trained on paired data of simple editing operations, which fundamentally limits their ability to gene... | 2026/pdf/Cong_VIVA_VLM-Guided_Instruction-Based_Video_Editing_with_Reward_Optimization_CVPR_2026_paper.pdf | @InProceedings{Cong_2026_CVPR,
author = {Cong, Xiaoyan and Yang, Haotian and Wang, Angtian and Wang, Yizhi and Yang, Yiding and Zhang, Canyu and Ma, Chongyang},
title = {VIVA: VLM-Guided Instruction-Based Video Editing with Reward Optimization},
booktitle = {Proceedings of the IEEE/CVF Conference on ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Cong_VIVA_VLM-Guided_Instruction-Based_Video_Editing_with_Reward_Optimization_CVPR_2026_paper.pdf |
Adaptive 3D Perception for Small Aerial Targets Under Sparse Sampling via Reinforcement Learning | Shenghai Yuan, Wei Yihan, Jason Yee, Zhuoran Qiao, boyang lou, Enwen Hu | Detecting small aerial targets (SATs) in long-range LiDAR is challenging because motion causes extreme variations in point density, breaking fixed-voxel and static-threshold assumptions in standard 3D detection and tracking. To address the challenges, we introduce A3PRL, an RL-driven adaptive perception framework that ... | 2026/pdf/Yuan_Adaptive_3D_Perception_for_Small_Aerial_Targets_Under_Sparse_Sampling_CVPR_2026_paper.pdf | @InProceedings{Yuan_2026_CVPR,
author = {Yuan, Shenghai and Yihan, Wei and Yee, Jason and Qiao, Zhuoran and lou, boyang and Hu, Enwen},
title = {Adaptive 3D Perception for Small Aerial Targets Under Sparse Sampling via Reinforcement Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Co... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yuan_Adaptive_3D_Perception_for_Small_Aerial_Targets_Under_Sparse_Sampling_CVPR_2026_paper.pdf |
FluxMem: Adaptive Hierarchical Memory for Streaming Video Understanding | Yiweng Xie, Bo He, Junke Wang, Xiangyu Zheng, Ziyi Ye, Zuxuan Wu | This paper presents FluxMem, a training-free framework for efficient streaming video understanding. FluxMem adaptively compresses redundant visual memory through a hierarchical, two-stage design: (1) a Temporal Adjacency Selection (TAS) module removes redundant visual tokens across adjacent frames, and (2) a Spatial Do... | 2026/pdf/Xie_FluxMem_Adaptive_Hierarchical_Memory_for_Streaming_Video_Understanding_CVPR_2026_paper.pdf | @InProceedings{Xie_2026_CVPR,
author = {Xie, Yiweng and He, Bo and Wang, Junke and Zheng, Xiangyu and Ye, Ziyi and Wu, Zuxuan},
title = {FluxMem: Adaptive Hierarchical Memory for Streaming Video Understanding},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xie_FluxMem_Adaptive_Hierarchical_Memory_for_Streaming_Video_Understanding_CVPR_2026_paper.pdf |
Convolutional Neural Networks Driven by Content Similarity | Ligeng Zou, Guihu Zhao | Although convolutional neural networks (CNNs) have continued to evolve in recent years, Transformers have become increasingly popular in the field of computer vision. In this work, we introduce a mechanism for CNNs to aggregate information based on content similarity--an ability analogous to the self-attention mechanis... | 2026/pdf/Zou_Convolutional_Neural_Networks_Driven_by_Content_Similarity_CVPR_2026_paper.pdf | @InProceedings{Zou_2026_CVPR,
author = {Zou, Ligeng and Zhao, Guihu},
title = {Convolutional Neural Networks Driven by Content Similarity},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2026},
pages... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zou_Convolutional_Neural_Networks_Driven_by_Content_Similarity_CVPR_2026_paper.pdf |
Focus on Background: Exploring SAM's Potential in Few-shot Medical Image Segmentation with Background-centric Prompting | Yuntian Bo, Yazhou Zhu, Piotr Koniusz, Haofeng Zhang | Conventional few-shot medical image segmentation (FSMIS) approaches face performance bottlenecks that hinder broader clinical applicability. Although the Segment Anything Model (SAM) exhibits strong category-agnostic segmentation capabilities, its direct application to medical images often leads to over-segmentation du... | 2026/pdf/Bo_Focus_on_Background_Exploring_SAMs_Potential_in_Few-shot_Medical_Image_CVPR_2026_paper.pdf | @InProceedings{Bo_2026_CVPR,
author = {Bo, Yuntian and Zhu, Yazhou and Koniusz, Piotr and Zhang, Haofeng},
title = {Focus on Background: Exploring SAM's Potential in Few-shot Medical Image Segmentation with Background-centric Prompting},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer... | https://openaccess.thecvf.com/content/CVPR2026/papers/Bo_Focus_on_Background_Exploring_SAMs_Potential_in_Few-shot_Medical_Image_CVPR_2026_paper.pdf |
Adapting In-context Generation for Enhanced Composed Image Retrieval | Haiwen Li, Zining Chen, Delong Liu, Zhaohui Hou, Zhicheng Zhao, Fei Su | As a challenge vision-language task, Composed Image Retrieval (CIR) aims to integrate information from a bi-modal query (image + text) to retrieve target images. While supervised CIR has achieved notable success in domain-specific scenarios, its reliance on manually annotated triplets restricts its scalability and appl... | 2026/pdf/Li_Adapting_In-context_Generation_for_Enhanced_Composed_Image_Retrieval_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Haiwen and Chen, Zining and Liu, Delong and Hou, Zhaohui and Zhao, Zhicheng and Su, Fei},
title = {Adapting In-context Generation for Enhanced Composed Image Retrieval},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_Adapting_In-context_Generation_for_Enhanced_Composed_Image_Retrieval_CVPR_2026_paper.pdf |
CoD: A Diffusion Foundation Model for Image Compression | Zhaoyang Jia, Zihan Zheng, Naifu Xue, Jiahao Li, Bin Li, Zongyu Guo, Xiaoyi Zhang, Houqiang Li, Yan Lu | Existing diffusion codecs typically build on text-to-image diffusion foundation models like Stable Diffusion.However, text conditioning is suboptimal from a compression perspective, hindering the potential of downstream diffusion codecs, particularly at ultra-low bitrates.To address it, we introduce CoD, the first Comp... | 2026/pdf/Jia_CoD_A_Diffusion_Foundation_Model_for_Image_Compression_CVPR_2026_paper.pdf | @InProceedings{Jia_2026_CVPR,
author = {Jia, Zhaoyang and Zheng, Zihan and Xue, Naifu and Li, Jiahao and Li, Bin and Guo, Zongyu and Zhang, Xiaoyi and Li, Houqiang and Lu, Yan},
title = {CoD: A Diffusion Foundation Model for Image Compression},
booktitle = {Proceedings of the IEEE/CVF Conference on C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Jia_CoD_A_Diffusion_Foundation_Model_for_Image_Compression_CVPR_2026_paper.pdf |
PEARL: Geometry Aligns Semantics for Training-Free Open-Vocabulary Semantic Segmentation | Gensheng Pei, Xiruo Jiang, Xinhao Cai, Tao Chen, Yazhou Yao, Byeungwoo Jeon | Training-free open-vocabulary semantic segmentation (OVSS) promises rapid adaptation to new label sets without retraining. Yet, many methods rely on heavy post-processing or handle text and vision in isolation, leaving cross-modal geometry underutilized. Others introduce auxiliary vision backbones or multi-model pipeli... | 2026/pdf/Pei_PEARL_Geometry_Aligns_Semantics_for_Training-Free_Open-Vocabulary_Semantic_Segmentation_CVPR_2026_paper.pdf | @InProceedings{Pei_2026_CVPR,
author = {Pei, Gensheng and Jiang, Xiruo and Cai, Xinhao and Chen, Tao and Yao, Yazhou and Jeon, Byeungwoo},
title = {PEARL: Geometry Aligns Semantics for Training-Free Open-Vocabulary Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Compute... | https://openaccess.thecvf.com/content/CVPR2026/papers/Pei_PEARL_Geometry_Aligns_Semantics_for_Training-Free_Open-Vocabulary_Semantic_Segmentation_CVPR_2026_paper.pdf |
CRFT: Consistent-Recurrent Feature Flow Transformer for Cross-Modal Image Registration | Xuecong Liu, Mengzhu Ding, Zixuan Sun, Zhang Li, Xichao Teng | We present Consistent-Recurrent Feature Flow Transformer (CRFT), a unified coarse-to-fine framework based on feature flow learning for robust cross-modal image registration. CRFT learns a modality-independent feature flow representation within a transformer-based architecture that jointly performs feature alignment and... | 2026/pdf/Liu_CRFT_Consistent-Recurrent_Feature_Flow_Transformer_for_Cross-Modal_Image_Registration_CVPR_2026_paper.pdf | @InProceedings{Liu_2026_CVPR,
author = {Liu, Xuecong and Ding, Mengzhu and Sun, Zixuan and Li, Zhang and Teng, Xichao},
title = {CRFT: Consistent-Recurrent Feature Flow Transformer for Cross-Modal Image Registration},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Liu_CRFT_Consistent-Recurrent_Feature_Flow_Transformer_for_Cross-Modal_Image_Registration_CVPR_2026_paper.pdf |
TGSFormer: Scalable Temporal Gaussian Splatting for Embodied Semantic Scene Completion | Rui Qian, Haozhi Cao, Tianchen Deng, Tianxin Hu, Weixiang Guo, Shenghai Yuan, Lihua Xie | Embodied 3D Semantic Scene Completion (SSC) infers dense geometry and semantics from continuous egocentric observations. Most existing Gaussian-based methods rely on random initialization of many primitives within predefined spatial bounds, resulting in redundancy and poor scalability to unbounded scenes. Recent depth-... | 2026/pdf/Qian_TGSFormer_Scalable_Temporal_Gaussian_Splatting_for_Embodied_Semantic_Scene_Completion_CVPR_2026_paper.pdf | @InProceedings{Qian_2026_CVPR,
author = {Qian, Rui and Cao, Haozhi and Deng, Tianchen and Hu, Tianxin and Guo, Weixiang and Yuan, Shenghai and Xie, Lihua},
title = {TGSFormer: Scalable Temporal Gaussian Splatting for Embodied Semantic Scene Completion},
booktitle = {Proceedings of the IEEE/CVF Confer... | https://openaccess.thecvf.com/content/CVPR2026/papers/Qian_TGSFormer_Scalable_Temporal_Gaussian_Splatting_for_Embodied_Semantic_Scene_Completion_CVPR_2026_paper.pdf |
ForceVLA2: Unleashing Hybrid Force-Position Control with Force Awareness for Contact-Rich Manipulation | Yang Li, Zhaxizhuoma Zhaxizhuoma, Hongru Jiang, Junjie Xia, Hongquan Zhang, Jinda Du, Yunsong Zhou, Jia Zeng, Ce Hao, Jieji Ren, Qiaojun Yu, Cewu Lu, Yu Qiao, Jiangmiao Pang | Embodied intelligence for contact-rich manipulation has predominantly relied on position control, while explicit awareness and regulation of interaction forces remain under-explored, limiting stability, precision, and robustness in real-world tasks. We propose ForceVLA2, an end-to-end vision-language-action framework t... | 2026/pdf/Li_ForceVLA2_Unleashing_Hybrid_Force-Position_Control_with_Force_Awareness_for_Contact-Rich_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Yang and Zhaxizhuoma, Zhaxizhuoma and Jiang, Hongru and Xia, Junjie and Zhang, Hongquan and Du, Jinda and Zhou, Yunsong and Zeng, Jia and Hao, Ce and Ren, Jieji and Yu, Qiaojun and Lu, Cewu and Qiao, Yu and Pang, Jiangmiao},
title = {ForceVLA2: Unleashing Hybrid... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_ForceVLA2_Unleashing_Hybrid_Force-Position_Control_with_Force_Awareness_for_Contact-Rich_CVPR_2026_paper.pdf |
VISTA: A Test-Time Self-Improving Video Generation Agent | Do Xuan Long, Xingchen Wan, Hootan Nakhost, Chen-Yu Lee, Tomas Pfister, Sercan Ö. Arik | Despite rapid advances in text-to-video synthesis, generated video quality remains critically dependent on precise user prompts. Existing test-time optimization methods, successful in other domains, struggle with the multi-faceted nature of video. In this work, we introduce VISTA (Video Iterative Self-improvemenT Agent... | 2026/pdf/Long_VISTA_A_Test-Time_Self-Improving_Video_Generation_Agent_CVPR_2026_paper.pdf | @InProceedings{Long_2026_CVPR,
author = {Long, Do Xuan and Wan, Xingchen and Nakhost, Hootan and Lee, Chen-Yu and Pfister, Tomas and Arik, Sercan \"O.},
title = {VISTA: A Test-Time Self-Improving Video Generation Agent},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patte... | https://openaccess.thecvf.com/content/CVPR2026/papers/Long_VISTA_A_Test-Time_Self-Improving_Video_Generation_Agent_CVPR_2026_paper.pdf |
Dynamic-Static Decomposition for Novel View Synthesis of Dynamic Scenes with Spiking Neurons | Lingyun Dai, Zehao Chen, Yan Liu, Shi Gu, Peng Lin, De Ma, Huajin Tang, Qian Zheng, Gang Pan | Novel view synthesis for dynamic scenes remains challenging due to complex motion variations. Recent methods represent dynamic and static regions with separate Gaussians to improve efficiency and accuracy, but inaccurate assignment of static and dynamic Gaussian primitives still limits performance. We identify two key ... | 2026/pdf/Dai_Dynamic-Static_Decomposition_for_Novel_View_Synthesis_of_Dynamic_Scenes_with_CVPR_2026_paper.pdf | @InProceedings{Dai_2026_CVPR,
author = {Dai, Lingyun and Chen, Zehao and Liu, Yan and Gu, Shi and Lin, Peng and Ma, De and Tang, Huajin and Zheng, Qian and Pan, Gang},
title = {Dynamic-Static Decomposition for Novel View Synthesis of Dynamic Scenes with Spiking Neurons},
booktitle = {Proceedings of t... | https://openaccess.thecvf.com/content/CVPR2026/papers/Dai_Dynamic-Static_Decomposition_for_Novel_View_Synthesis_of_Dynamic_Scenes_with_CVPR_2026_paper.pdf |
Unleashing Vision-Language Semantics for Deepfake Video Detection | Jiawen Zhu, Yunqi Miao, Xueyi Zhang, Jiankang Deng, Guansong Pang | Recent Deepfake Video Detection (DFD) studies have demonstrated that pre-trained Vision-Language Models (VLMs) such as CLIP exhibit strong generalization capabilities in detecting artifacts across different identities. However, existing approaches focus on leveraging visual features only, overlooking their most distinc... | 2026/pdf/Zhu_Unleashing_Vision-Language_Semantics_for_Deepfake_Video_Detection_CVPR_2026_paper.pdf | @InProceedings{Zhu_2026_CVPR,
author = {Zhu, Jiawen and Miao, Yunqi and Zhang, Xueyi and Deng, Jiankang and Pang, Guansong},
title = {Unleashing Vision-Language Semantics for Deepfake Video Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVP... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhu_Unleashing_Vision-Language_Semantics_for_Deepfake_Video_Detection_CVPR_2026_paper.pdf |
Hierarchical Visual Relocalization with Nearest View Synthesis from Feature Gaussian Splatting | Huaqi Tao, Bingxi Liu, Guangcheng Chen, Fulin Tang, Li He, Hong Zhang | Visual relocalization is a fundamental task in the field of 3D computer vision, estimating a camera's pose when it revisits a previously known scene. While point-based hierarchical relocalization methods have shown strong scalability and efficiency, they are often limited by sparse image observations and weak feature m... | 2026/pdf/Tao_Hierarchical_Visual_Relocalization_with_Nearest_View_Synthesis_from_Feature_Gaussian_CVPR_2026_paper.pdf | @InProceedings{Tao_2026_CVPR,
author = {Tao, Huaqi and Liu, Bingxi and Chen, Guangcheng and Tang, Fulin and He, Li and Zhang, Hong},
title = {Hierarchical Visual Relocalization with Nearest View Synthesis from Feature Gaussian Splatting},
booktitle = {Proceedings of the IEEE/CVF Conference on Compute... | https://openaccess.thecvf.com/content/CVPR2026/papers/Tao_Hierarchical_Visual_Relocalization_with_Nearest_View_Synthesis_from_Feature_Gaussian_CVPR_2026_paper.pdf |
Protect to Adapt: Orthogonal Subspace Control with Ranked Negative-Prompt Curriculum for Few-Shot Action Recognition | Hantao Qi, Yan Yan, Junlong Gao, Hanzi Wang | Adapting Vision-Language Models (VLMs) to few-shot action recognition (FSAR) often trades accuracy for stability: task-specific gains can trigger catastrophic forgetting of domain-general knowledge and reduce inter-class margins. In few-shot episodes, each query is contrasted with only one positive class and a few nega... | 2026/pdf/Qi_Protect_to_Adapt_Orthogonal_Subspace_Control_with_Ranked_Negative-Prompt_Curriculum_CVPR_2026_paper.pdf | @InProceedings{Qi_2026_CVPR,
author = {Qi, Hantao and Yan, Yan and Gao, Junlong and Wang, Hanzi},
title = {Protect to Adapt: Orthogonal Subspace Control with Ranked Negative-Prompt Curriculum for Few-Shot Action Recognition},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Qi_Protect_to_Adapt_Orthogonal_Subspace_Control_with_Ranked_Negative-Prompt_Curriculum_CVPR_2026_paper.pdf |
Differentially Private 2D Human Pose Estimation | Kaushik Bhargav Sivangi, Paul Henderson, Fani Deligianni | Human pose estimation (HPE) underpins critical applications in healthcare, activity recognition, and human-computer interaction. However, the privacy implications of processing sensitive visual data present significant deployment barriers in critical domains. %Conventional anonymization techniques offer weak protection... | 2026/pdf/Sivangi_Differentially_Private_2D_Human_Pose_Estimation_CVPR_2026_paper.pdf | @InProceedings{Sivangi_2026_CVPR,
author = {Sivangi, Kaushik Bhargav and Henderson, Paul and Deligianni, Fani},
title = {Differentially Private 2D Human Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Sivangi_Differentially_Private_2D_Human_Pose_Estimation_CVPR_2026_paper.pdf |
MaskFocus: Focusing Policy Optimization on Critical Steps for Masked Image Generation | Guohui Zhang, Hu Yu, Xiaoxiao Ma, Yaning Pan, Hang Xu, Jie Huang, Feng Zhao | Reinforcement learning (RL) has demonstrated significant potential for post-training language models and autoregressive visual generative models, but adapting RL to masked generative models (MGMs) remains challenging. The core factor is that policy optimization requires the probability likelihood of each step due to it... | 2026/pdf/Zhang_MaskFocus_Focusing_Policy_Optimization_on_Critical_Steps_for_Masked_Image_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Guohui and Yu, Hu and Ma, Xiaoxiao and Pan, Yaning and Xu, Hang and Huang, Jie and Zhao, Feng},
title = {MaskFocus: Focusing Policy Optimization on Critical Steps for Masked Image Generation},
booktitle = {Proceedings of the IEEE/CVF Conference on Comp... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_MaskFocus_Focusing_Policy_Optimization_on_Critical_Steps_for_Masked_Image_CVPR_2026_paper.pdf |
Uni-Hema: Unified Model for Digital Hematopathology | Abdul Rehman, Iqra Rasool, Ayisha Imran, Mohsen Ali, Waqas Sultani | Digital hematopathology requires cell-level analysis across diverse disease categories, including malignant disorders (e.g., leukemia), infectious conditions (e.g., malaria), and non-malignant red blood cell disorders (e.g., sickle cell disease). Whether single-task, vision-language, WSI- optimized, or single-cell hema... | 2026/pdf/Rehman_Uni-Hema_Unified_Model_for_Digital_Hematopathology_CVPR_2026_paper.pdf | @InProceedings{Rehman_2026_CVPR,
author = {Rehman, Abdul and Rasool, Iqra and Imran, Ayisha and Ali, Mohsen and Sultani, Waqas},
title = {Uni-Hema: Unified Model for Digital Hematopathology},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
m... | https://openaccess.thecvf.com/content/CVPR2026/papers/Rehman_Uni-Hema_Unified_Model_for_Digital_Hematopathology_CVPR_2026_paper.pdf |
MetricHMSR: Metric Human Mesh and Scene Recovery from Monocular Images | Chentao Song, He Zhang, Haolei Yuan, Haozhe Lin, Jianhua Tao, Hongwen Zhang, Tao Yu | We introduce MetricHMSR (Metric Human Mesh and Scene Recovery), a novel approach for metric human mesh and scene recovery from monocular images. Due to unrealistic assumptions in the camera model and inherent challenges in metric perception, existing approaches struggle to achieve human pose and metric 3D position esti... | 2026/pdf/Song_MetricHMSR_Metric_Human_Mesh_and_Scene_Recovery_from_Monocular_Images_CVPR_2026_paper.pdf | @InProceedings{Song_2026_CVPR,
author = {Song, Chentao and Zhang, He and Yuan, Haolei and Lin, Haozhe and Tao, Jianhua and Zhang, Hongwen and Yu, Tao},
title = {MetricHMSR: Metric Human Mesh and Scene Recovery from Monocular Images},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vis... | https://openaccess.thecvf.com/content/CVPR2026/papers/Song_MetricHMSR_Metric_Human_Mesh_and_Scene_Recovery_from_Monocular_Images_CVPR_2026_paper.pdf |
ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding | Jovana Kondic, Pengyuan Li, Dhiraj Joshi, Isaac Sanchez, Ben Wiesel, Shafiq Abedin, Amit Alfassy, Eli Schwartz, Daniel Caraballo, Yagmur Gizem Cinar, Florian Scheidegger, Steven I. Ross, Daniel Karl I. Weidele, Hang Hua, Ekaterina Arutyunova, Roei Herzig, Zihan Wang, Xinyue Yu, Yunfei Zhao, Sicong Jiang, Minghao Liu, Q... | Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a capability where current vision-language models (VLMs) remain limited. We introduce ChartNet, a high-quality, million-scale multimodal dataset designed to advance chart interpretat... | 2026/pdf/Kondic_ChartNet_A_Million-Scale_High-Quality_Multimodal_Dataset_for_Robust_Chart_Understanding_CVPR_2026_paper.pdf | @InProceedings{Kondic_2026_CVPR,
author = {Kondic, Jovana and Li, Pengyuan and Joshi, Dhiraj and Sanchez, Isaac and Wiesel, Ben and Abedin, Shafiq and Alfassy, Amit and Schwartz, Eli and Caraballo, Daniel and Cinar, Yagmur Gizem and Scheidegger, Florian and Ross, Steven I. and Weidele, Daniel Karl I. and Hua, Ha... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kondic_ChartNet_A_Million-Scale_High-Quality_Multimodal_Dataset_for_Robust_Chart_Understanding_CVPR_2026_paper.pdf |
GraspGen-X: Cross-Embodiment 6-DOF Diffusion-based Grasping | Beining Han, Yu-Wei Chao, Erwin Coumans, Clemens Eppner, Jia Deng, Stan Birchfield, Adithyavairavan Murali | We study cross-embodiment 6-DOF robot grasping. Unlike prior works, we require the model not only to generalize to novel objects / scenes but also to novel gripper morphologies and physical grasping processes. Our method extends diffusion model based generative 6-DOF grasping models to condition on the additional gripp... | 2026/pdf/Han_GraspGen-X_Cross-Embodiment_6-DOF_Diffusion-based_Grasping_CVPR_2026_paper.pdf | @InProceedings{Han_2026_CVPR,
author = {Han, Beining and Chao, Yu-Wei and Coumans, Erwin and Eppner, Clemens and Deng, Jia and Birchfield, Stan and Murali, Adithyavairavan},
title = {GraspGen-X: Cross-Embodiment 6-DOF Diffusion-based Grasping},
booktitle = {Proceedings of the IEEE/CVF Conference on C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Han_GraspGen-X_Cross-Embodiment_6-DOF_Diffusion-based_Grasping_CVPR_2026_paper.pdf |
MapRoute:Precise-Concept Erasing Mappers via Semantic Routing | Sihao Li, Baixi Liang, Shuohong Xia, Yunyun Yang | Contemporary commercial and open-source diffusion models have demonstrated remarkable performance in text-to-image generation, enabling widespread applications in creative design and content creation. However, legitimate requirements--such as copyright protection, privacy compliance, or personalized customization--ofte... | 2026/pdf/Li_MapRoutePrecise-Concept_Erasing_Mappers_via_Semantic_Routing_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Sihao and Liang, Baixi and Xia, Shuohong and Yang, Yunyun},
title = {MapRoute:Precise-Concept Erasing Mappers via Semantic Routing},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_MapRoutePrecise-Concept_Erasing_Mappers_via_Semantic_Routing_CVPR_2026_paper.pdf |
Not All Birds Look The Same: Identity-Preserving Generation For Birds | Aaron Sun, Oindrila Saha, Subhransu Maji | Since the advent of controllable image generation, increasingly rich modes of control have enabled greater customization and accessibility for everyday users.Zero-shot, identity-preserving models such as Insert Anything and OminiControl now support applications like virtual try-on without requiring additional fine-tuni... | 2026/pdf/Sun_Not_All_Birds_Look_The_Same_Identity-Preserving_Generation_For_Birds_CVPR_2026_paper.pdf | @InProceedings{Sun_2026_CVPR,
author = {Sun, Aaron and Saha, Oindrila and Maji, Subhransu},
title = {Not All Birds Look The Same: Identity-Preserving Generation For Birds},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Sun_Not_All_Birds_Look_The_Same_Identity-Preserving_Generation_For_Birds_CVPR_2026_paper.pdf |
Geometric-Aware Hypergraph Reasoning for Novel Class Discovery in Point Cloud Segmentation | Zihao Zhang, Aming Wu, Yang Li, Yahong Han, Jialie Shen | Novel Class Discovery in Point Cloud Segmentation is recently proposed, aiming to leverage knowledge from known classes to automatically segment unlabeled classes within point clouds. The core of this task lies in leveraging the geometric and semantic knowledge of multiple known classes to achieve semantic understandin... | 2026/pdf/Zhang_Geometric-Aware_Hypergraph_Reasoning_for_Novel_Class_Discovery_in_Point_Cloud_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Zihao and Wu, Aming and Li, Yang and Han, Yahong and Shen, Jialie},
title = {Geometric-Aware Hypergraph Reasoning for Novel Class Discovery in Point Cloud Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_Geometric-Aware_Hypergraph_Reasoning_for_Novel_Class_Discovery_in_Point_Cloud_CVPR_2026_paper.pdf |
Discriminative Perception via Anchored Description for Reasoning Segmentation | Tao Yang, Qing Zhou, Yanliang Li, Qi Wang | Reasoning segmentation increasingly employs reinforcement learning to generate explanatory reasoning chains that guide Multimodal Large Language Models. While these geometric rewards are primarily confined to guiding the final localization, they are incapable of discriminating whether the reasoning process remains anch... | 2026/pdf/Yang_Discriminative_Perception_via_Anchored_Description_for_Reasoning_Segmentation_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Tao and Zhou, Qing and Li, Yanliang and Wang, Qi},
title = {Discriminative Perception via Anchored Description for Reasoning Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_Discriminative_Perception_via_Anchored_Description_for_Reasoning_Segmentation_CVPR_2026_paper.pdf |
Dual Band Thermal Videography: Separating Time-Varying Reflection and Emission Near Ambient Conditions | Sriram Narayanan, Mani Ramanagopal, Srinivasa Narasimhan | Long-wave infrared radiation captured by a thermal camera includes (a) emission from an object governed by its temperature and emissivity, and (b) reflected radiation from the surrounding environment. Separating these components is a long-standing challenge in thermography. Even when using multiple bands, the problem i... | 2026/pdf/Narayanan_Dual_Band_Thermal_Videography_Separating_Time-Varying_Reflection_and_Emission_Near_CVPR_2026_paper.pdf | @InProceedings{Narayanan_2026_CVPR,
author = {Narayanan, Sriram and Ramanagopal, Mani and Narasimhan, Srinivasa},
title = {Dual Band Thermal Videography: Separating Time-Varying Reflection and Emission Near Ambient Conditions},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision an... | https://openaccess.thecvf.com/content/CVPR2026/papers/Narayanan_Dual_Band_Thermal_Videography_Separating_Time-Varying_Reflection_and_Emission_Near_CVPR_2026_paper.pdf |
Breaking the Continuum: Discrete Distribution Learning for Structural MRI Reconstruction | Tianle Lyu, Mengjingcheng Mo, Ting Wen, Zhen Song, Zinan Xiong, Yanjie Zhu | Anatomical structures in MRI exhibit strong spatial priors, including well-defined boundaries, low inter-subject variability, and consistent topology. These properties naturally induce clustered patterns in the latent space, which are difficult to capture using conventional continuous generative priors that assume smoo... | 2026/pdf/Lyu_Breaking_the_Continuum_Discrete_Distribution_Learning_for_Structural_MRI_Reconstruction_CVPR_2026_paper.pdf | @InProceedings{Lyu_2026_CVPR,
author = {Lyu, Tianle and Mo, Mengjingcheng and Wen, Ting and Song, Zhen and Xiong, Zinan and Zhu, Yanjie},
title = {Breaking the Continuum: Discrete Distribution Learning for Structural MRI Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lyu_Breaking_the_Continuum_Discrete_Distribution_Learning_for_Structural_MRI_Reconstruction_CVPR_2026_paper.pdf |
H2-Surv: Hierarchical Hyperbolic Multimodal Representation Learning for Survival Prediction | Jiaqi Yang, Wenting Chen, Xiangjian He, Yuanbai Li, Sen Yang, Linlin Shen, Xiaohan Xing | Cancer survival prediction through multimodal learning that combines histopathology images with genomic data represents a promising research direction. However, current approaches still suffer from two key limitations. First, most methods operate in a Euclidean feature space, which makes it difficult to capture the int... | 2026/pdf/Yang_H2-Surv_Hierarchical_Hyperbolic_Multimodal_Representation_Learning_for_Survival_Prediction_CVPR_2026_paper.pdf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Jiaqi and Chen, Wenting and He, Xiangjian and Li, Yuanbai and Yang, Sen and Shen, Linlin and Xing, Xiaohan},
title = {H2-Surv: Hierarchical Hyperbolic Multimodal Representation Learning for Survival Prediction},
booktitle = {Proceedings of the IEEE/CVF C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_H2-Surv_Hierarchical_Hyperbolic_Multimodal_Representation_Learning_for_Survival_Prediction_CVPR_2026_paper.pdf |
SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving | Peizheng Li, Zhenghao Zhang, David Holtz, Hang Yu, Yutong Yang, Yuzhi Lai, Rui Song, Andreas Geiger, Andreas Zell | End-to-end autonomous driving methods built on vision language models (VLMs) have undergone rapid development driven by their universal visual understanding and strong reasoning capabilities obtained from the large-scale pretraining. However, we find that current VLMs struggle to understand fine-grained 3D spatial rela... | 2026/pdf/Li_SpaceDrive_Infusing_Spatial_Awareness_into_VLM-based_Autonomous_Driving_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Peizheng and Zhang, Zhenghao and Holtz, David and Yu, Hang and Yang, Yutong and Lai, Yuzhi and Song, Rui and Geiger, Andreas and Zell, Andreas},
title = {SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving},
booktitle = {Proceedings of t... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_SpaceDrive_Infusing_Spatial_Awareness_into_VLM-based_Autonomous_Driving_CVPR_2026_paper.pdf |
CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval | Jiahui Geng, Qing Li, Fengyu Cai, Fakhri Karray | Code search, framed as information retrieval (IR), underpins modern software engineering and increasingly powers retrieval-augmented generation (RAG), improving code discovery, reuse, and the reliability of LLM-based coding.Yet existing code IR models remain largely text-centric and often overlook the visual and struct... | 2026/pdf/Geng_CodeMMR_Bridging_Natural_Language_Code_and_Image_for_Unified_Retrieval_CVPR_2026_paper.pdf | @InProceedings{Geng_2026_CVPR,
author = {Geng, Jiahui and Li, Qing and Cai, Fengyu and Karray, Fakhri},
title = {CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
mont... | https://openaccess.thecvf.com/content/CVPR2026/papers/Geng_CodeMMR_Bridging_Natural_Language_Code_and_Image_for_Unified_Retrieval_CVPR_2026_paper.pdf |
Beyond Explicit Language: Plug-and-Play Visual-to-Linguistic Modeling Toward General Object Tracking | Kaiyang Lan, Ying Cui, Chenchen Jing, Jianwei Zheng, Dongyan Guo | Natural language provides valuable auxiliary information for enhancing visual object tracking. While existing vision-language tracking methods explicitly leverage linguistic descriptions to aid tracking, they suffer from two critical limitations: the inability to dynamically adapt descriptions to the moving target and ... | 2026/pdf/Lan_Beyond_Explicit_Language_Plug-and-Play_Visual-to-Linguistic_Modeling_Toward_General_Object_Tracking_CVPR_2026_paper.pdf | @InProceedings{Lan_2026_CVPR,
author = {Lan, Kaiyang and Cui, Ying and Jing, Chenchen and Zheng, Jianwei and Guo, Dongyan},
title = {Beyond Explicit Language: Plug-and-Play Visual-to-Linguistic Modeling Toward General Object Tracking},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer V... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lan_Beyond_Explicit_Language_Plug-and-Play_Visual-to-Linguistic_Modeling_Toward_General_Object_Tracking_CVPR_2026_paper.pdf |
RemedyGS: Defend 3D Gaussian Splatting Against Computation Cost Attacks | Yanping Li, Zhening Liu, Zijian Li, Zehong Lin, Jun Zhang | As a mainstream technique for 3D reconstruction, 3D Gaussian splatting (3DGS) has been applied in a wide range of applications and services. Recent studies have revealed critical vulnerabilities in this pipeline and introduced computation cost attacks that lead to malicious resource occupancies and even denial-of-servi... | 2026/pdf/Li_RemedyGS_Defend_3D_Gaussian_Splatting_Against_Computation_Cost_Attacks_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Yanping and Liu, Zhening and Li, Zijian and Lin, Zehong and Zhang, Jun},
title = {RemedyGS: Defend 3D Gaussian Splatting Against Computation Cost Attacks},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_RemedyGS_Defend_3D_Gaussian_Splatting_Against_Computation_Cost_Attacks_CVPR_2026_paper.pdf |
DRAMA: Next-Gen Dynamic Orchestration for Resilient Multi-Agent Ecosystems in Flux | Xinkui Zhao, Yifan Zhang, Sai Liu, Naibo Wang, Guanjie Cheng, Yueshen Xu, Chang Liu, Shuiguang Deng, Jianwei Yin | Embodied Multi-Agent Systems have proven highly effective in addressing complex tasks through coordinated collaboration among heterogeneous agents. However, real-world environments and task specifications are inherently dynamic, exhibiting frequent changes, uncertainty, and variability. Despite these characteristics, m... | 2026/pdf/Zhao_DRAMA_Next-Gen_Dynamic_Orchestration_for_Resilient_Multi-Agent_Ecosystems_in_Flux_CVPR_2026_paper.pdf | @InProceedings{Zhao_2026_CVPR,
author = {Zhao, Xinkui and Zhang, Yifan and Liu, Sai and Wang, Naibo and Cheng, Guanjie and Xu, Yueshen and Liu, Chang and Deng, Shuiguang and Yin, Jianwei},
title = {DRAMA: Next-Gen Dynamic Orchestration for Resilient Multi-Agent Ecosystems in Flux},
booktitle = {Proce... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhao_DRAMA_Next-Gen_Dynamic_Orchestration_for_Resilient_Multi-Agent_Ecosystems_in_Flux_CVPR_2026_paper.pdf |
BiProLoRA: Bilevel Prompt LoRA for Real Scene Recovery | Nan An, Long Ma, Tengyu Ma, Zhu Liu, Yingchi Liu, Risheng Liu | The emergence of large generative models has substantially advanced learning-based scene recovery in the synthetic domain. However, these models generalize poorly to real scenarios stemming from the significant distribution gap, alongside poor adaptation to complex and unforeseen degradations. Consequently, it is imper... | 2026/pdf/An_BiProLoRA_Bilevel_Prompt_LoRA_for_Real_Scene_Recovery_CVPR_2026_paper.pdf | @InProceedings{An_2026_CVPR,
author = {An, Nan and Ma, Long and Ma, Tengyu and Liu, Zhu and Liu, Yingchi and Liu, Risheng},
title = {BiProLoRA: Bilevel Prompt LoRA for Real Scene Recovery},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
mon... | https://openaccess.thecvf.com/content/CVPR2026/papers/An_BiProLoRA_Bilevel_Prompt_LoRA_for_Real_Scene_Recovery_CVPR_2026_paper.pdf |
Benchmarking Endoscopic Surgical Image Restoration and Beyond | Jialun Pei, Diandian Guo, Donghui Yang, Zhixi Li, Yuxin Feng, Long Ma, Bo Du, Pheng-Ann Heng | In endoscopic surgery, a clear and high-quality visual field is critical for surgeons to make accurate intraoperative decisions. However, persistent visual degradation, including smoke generated by energy devices, lens fogging from thermal gradients, and lens contamination due to blood or tissue fluid splashes during s... | 2026/pdf/Pei_Benchmarking_Endoscopic_Surgical_Image_Restoration_and_Beyond_CVPR_2026_paper.pdf | @InProceedings{Pei_2026_CVPR,
author = {Pei, Jialun and Guo, Diandian and Yang, Donghui and Li, Zhixi and Feng, Yuxin and Ma, Long and Du, Bo and Heng, Pheng-Ann},
title = {Benchmarking Endoscopic Surgical Image Restoration and Beyond},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Pei_Benchmarking_Endoscopic_Surgical_Image_Restoration_and_Beyond_CVPR_2026_paper.pdf |
EagleVision: A Dual-Stage Framework with BEV-grounding-based Chain-of-Thought for Spatial Intelligence | Jiaxu Wan, Xu Wang, Mengwei Xie, Hang Zhang, Mu Xu, Yang Han, Ding Yuan, Hong Zhang, Yifan Yang | Video-based spatial reasoning -- such as estimating distances, judging directions, or understanding layouts from multiple views -- requires selecting informative frames and, when needed, actively seeking additional viewpoints during inference. Existing multimodal large language models (MLLMs) consume a fixed set of uni... | 2026/pdf/Wan_EagleVision_A_Dual-Stage_Framework_with_BEV-grounding-based_Chain-of-Thought_for_Spatial_Intelligence_CVPR_2026_paper.pdf | @InProceedings{Wan_2026_CVPR,
author = {Wan, Jiaxu and Wang, Xu and Xie, Mengwei and Zhang, Hang and Xu, Mu and Han, Yang and Yuan, Ding and Zhang, Hong and Yang, Yifan},
title = {EagleVision: A Dual-Stage Framework with BEV-grounding-based Chain-of-Thought for Spatial Intelligence},
booktitle = {Pro... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wan_EagleVision_A_Dual-Stage_Framework_with_BEV-grounding-based_Chain-of-Thought_for_Spatial_Intelligence_CVPR_2026_paper.pdf |
OneStory: Coherent Multi-Shot Video Generation with Adaptive Memory | Zhaochong An, Menglin Jia, Haonan Qiu, Zijian Zhou, Xiaoke Huang, Zhiheng Liu, Weiming Ren, Kumara Kahatapitiya, Ding Liu, Sen He, Chenyang Zhang, Tao Xiang, Fanny Yang, Serge Belongie, Tian Xie | Storytelling in real-world videos often unfolds through multiple shots--discontinuous yet semantically connected clips that together convey a coherent narrative. However, existing multi-shot video generation (MSV) methods struggle to effectively model long-range cross-shot context, as they rely on limited temporal wind... | 2026/pdf/An_OneStory_Coherent_Multi-Shot_Video_Generation_with_Adaptive_Memory_CVPR_2026_paper.pdf | @InProceedings{An_2026_CVPR,
author = {An, Zhaochong and Jia, Menglin and Qiu, Haonan and Zhou, Zijian and Huang, Xiaoke and Liu, Zhiheng and Ren, Weiming and Kahatapitiya, Kumara and Liu, Ding and He, Sen and Zhang, Chenyang and Xiang, Tao and Yang, Fanny and Belongie, Serge and Xie, Tian},
title = {One... | https://openaccess.thecvf.com/content/CVPR2026/papers/An_OneStory_Coherent_Multi-Shot_Video_Generation_with_Adaptive_Memory_CVPR_2026_paper.pdf |
Tavatar: Topology-Aware Gaussian Attribute Derivation for Animatable Human Avatars | Hailin Luo, Yifan Yang, Jiazhi Shu, Zixiong Huang, Qi Chen, Qing Du, Mingkui Tan | Reconstructing high-fidelity, animatable human avatars from monocular videos remains a critical challenge. Existing 3DGS-based human animation methods constrain Gaussian parameters but exclude scale, which we argue is crucial for adapting human poses to challenging out-of-distribution poses. To achieve robust animation... | 2026/pdf/Luo_Tavatar_Topology-Aware_Gaussian_Attribute_Derivation_for_Animatable_Human_Avatars_CVPR_2026_paper.pdf | @InProceedings{Luo_2026_CVPR,
author = {Luo, Hailin and Yang, Yifan and Shu, Jiazhi and Huang, Zixiong and Chen, Qi and Du, Qing and Tan, Mingkui},
title = {Tavatar: Topology-Aware Gaussian Attribute Derivation for Animatable Human Avatars},
booktitle = {Proceedings of the IEEE/CVF Conference on Comp... | https://openaccess.thecvf.com/content/CVPR2026/papers/Luo_Tavatar_Topology-Aware_Gaussian_Attribute_Derivation_for_Animatable_Human_Avatars_CVPR_2026_paper.pdf |
From Weights to Concepts: Data-Free Interpretability of CLIP via Singular Vector Decomposition | Francesco Gentile, Nicola Dall'Asen, Francesco Tonini, Massimiliano Mancini, Lorenzo Vaquero, Elisa Ricci | As vision-language models are deployed at scale, understanding their internal mechanisms becomes increasingly critical. Existing interpretability methods predominantly rely on activations, making them dataset-dependent, vulnerable to data bias, and often restricted to coarse head-level explanations. We introduce SITH (... | 2026/pdf/Gentile_From_Weights_to_Concepts_Data-Free_Interpretability_of_CLIP_via_Singular_CVPR_2026_paper.pdf | @InProceedings{Gentile_2026_CVPR,
author = {Gentile, Francesco and Dall'Asen, Nicola and Tonini, Francesco and Mancini, Massimiliano and Vaquero, Lorenzo and Ricci, Elisa},
title = {From Weights to Concepts: Data-Free Interpretability of CLIP via Singular Vector Decomposition},
booktitle = {Proceedin... | https://openaccess.thecvf.com/content/CVPR2026/papers/Gentile_From_Weights_to_Concepts_Data-Free_Interpretability_of_CLIP_via_Singular_CVPR_2026_paper.pdf |
OMoBlur: An Object Motion Blur Dataset and Benchmark for Real-World Local Motion Deblurring | Dingchuan Yu, Jiatong Li, Jingwen Zhou, Zhengyue Zhuge, Yueting Chen, Qi Li | Object motion blur in static scenes is spatially heterogeneous, differing from conventional deblurring problems yet frequently occurring in real handheld capture scenarios. Existing datasets either rely on costly beam-splitting capture with residual misalignment or employ synthetic blur that fails to model the continuo... | 2026/pdf/Yu_OMoBlur_An_Object_Motion_Blur_Dataset_and_Benchmark_for_Real-World_CVPR_2026_paper.pdf | @InProceedings{Yu_2026_CVPR,
author = {Yu, Dingchuan and Li, Jiatong and Zhou, Jingwen and Zhuge, Zhengyue and Chen, Yueting and Li, Qi},
title = {OMoBlur: An Object Motion Blur Dataset and Benchmark for Real-World Local Motion Deblurring},
booktitle = {Proceedings of the IEEE/CVF Conference on Compu... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yu_OMoBlur_An_Object_Motion_Blur_Dataset_and_Benchmark_for_Real-World_CVPR_2026_paper.pdf |
StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic Datasets | Anh-Quan Cao, Ivan Lopes, Raoul de Charette | Multi-task learning for dense prediction is limited by the need for extensive annotation for every task, although recent works have explored training with partial task labels. Leveraging the generalization power of diffusion models, we extend the partial learning setup to a zero-shot setting, training a multi-task mode... | 2026/pdf/Cao_StableMTL_Repurposing_Latent_Diffusion_Models_for_Multi-Task_Learning_from_Partially_CVPR_2026_paper.pdf | @InProceedings{Cao_2026_CVPR,
author = {Cao, Anh-Quan and Lopes, Ivan and de Charette, Raoul},
title = {StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic Datasets},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patte... | https://openaccess.thecvf.com/content/CVPR2026/papers/Cao_StableMTL_Repurposing_Latent_Diffusion_Models_for_Multi-Task_Learning_from_Partially_CVPR_2026_paper.pdf |
Locate-then-Sparsify: Attribution Guided Sparse Strategy for Visual Hallucination Mitigation | Tiantian Dang, Chao Bi, Shufan Shen, Jinzhe Liu, Qingming Huang, Shuhui Wang | Despite the significant advancements in Large Vision-Language Models (LVLMs), their tendency to generate hallucinations undermines reliability and restricts broader practical deployment. Among the hallucination mitigation methods, feature steering emerges as a promising approach that reduces erroneous outputs in LVLMs ... | 2026/pdf/Dang_Locate-then-Sparsify_Attribution_Guided_Sparse_Strategy_for_Visual_Hallucination_Mitigation_CVPR_2026_paper.pdf | @InProceedings{Dang_2026_CVPR,
author = {Dang, Tiantian and Bi, Chao and Shen, Shufan and Liu, Jinzhe and Huang, Qingming and Wang, Shuhui},
title = {Locate-then-Sparsify: Attribution Guided Sparse Strategy for Visual Hallucination Mitigation},
booktitle = {Proceedings of the IEEE/CVF Conference on C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Dang_Locate-then-Sparsify_Attribution_Guided_Sparse_Strategy_for_Visual_Hallucination_Mitigation_CVPR_2026_paper.pdf |
Spectral Conformal Risk Control: Distribution-Free Tail Guarantees via Bayesian Quadrature | Mohammad Mahdi Kazemi Esfeh, Qi Yan, Yongxing Zhang, Zahra Gholami, Renjie Liao, Purang Abolmaesumi | Modern vision systems are deployed in settings where occasional catastrophic failures matter more than average accuracy--for example in medical imaging, autonomous driving, and safety monitoring. While conformal prediction gives distribution-free uncertainty guarantees, most existing methods only control mean error and... | 2026/pdf/Esfeh_Spectral_Conformal_Risk_Control_Distribution-Free_Tail_Guarantees_via_Bayesian_Quadrature_CVPR_2026_paper.pdf | @InProceedings{Esfeh_2026_CVPR,
author = {Esfeh, Mohammad Mahdi Kazemi and Yan, Qi and Zhang, Yongxing and Gholami, Zahra and Liao, Renjie and Abolmaesumi, Purang},
title = {Spectral Conformal Risk Control: Distribution-Free Tail Guarantees via Bayesian Quadrature},
booktitle = {Proceedings of the IE... | https://openaccess.thecvf.com/content/CVPR2026/papers/Esfeh_Spectral_Conformal_Risk_Control_Distribution-Free_Tail_Guarantees_via_Bayesian_Quadrature_CVPR_2026_paper.pdf |
Beyond Rule-Based Agents: Active Markov Games for Realistic Multi-Agent Interaction in Autonomous Driving | Yuan Gui, Hongchen Luo, Jiao Wang, Liqi Qu | Current research in autonomous driving heavily relies on large-scale driving datasets for model fitting or trial-and-error learning strategies in simulation environments. However, these approaches suffer from limited behavioral diversity and fail to cover complex edge-case interactions. To address these limitations, we... | 2026/pdf/Gui_Beyond_Rule-Based_Agents_Active_Markov_Games_for_Realistic_Multi-Agent_Interaction_CVPR_2026_paper.pdf | @InProceedings{Gui_2026_CVPR,
author = {Gui, Yuan and Luo, Hongchen and Wang, Jiao and Qu, Liqi},
title = {Beyond Rule-Based Agents: Active Markov Games for Realistic Multi-Agent Interaction in Autonomous Driving},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Rec... | https://openaccess.thecvf.com/content/CVPR2026/papers/Gui_Beyond_Rule-Based_Agents_Active_Markov_Games_for_Realistic_Multi-Agent_Interaction_CVPR_2026_paper.pdf |
VideoChat-M1: Collaborative Policy Planning for Video Understanding via Multi-Agent Reinforcement Learning | Boyu Chen, Zikang Wang, Zhengrong Yue, Kainan Yan, Chenyun Yu, Yi Huang, Zijun Liu, Yafei Wen, Xiaoxin Chen, Yang Liu, Peng Li, Yali Wang | Most of the multi-agent video understanding frameworks adopt static and non-learnable tool invocation mechanisms, which limit the discovery of diverse clues essential for robust perception and reasoning regarding temporally or spatially complex videos. To address this challenge, we propose a novel Multi-agent system fo... | 2026/pdf/Chen_VideoChat-M1_Collaborative_Policy_Planning_for_Video_Understanding_via_Multi-Agent_Reinforcement_CVPR_2026_paper.pdf | @InProceedings{Chen_2026_CVPR,
author = {Chen, Boyu and Wang, Zikang and Yue, Zhengrong and Yan, Kainan and Yu, Chenyun and Huang, Yi and Liu, Zijun and Wen, Yafei and Chen, Xiaoxin and Liu, Yang and Li, Peng and Wang, Yali},
title = {VideoChat-M1: Collaborative Policy Planning for Video Understanding vi... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chen_VideoChat-M1_Collaborative_Policy_Planning_for_Video_Understanding_via_Multi-Agent_Reinforcement_CVPR_2026_paper.pdf |
Cycle-Consistent Tuning for Layered Image Decomposition | Zheng Gu, Min Lu, Zhida Sun, Dani Lischinski, Daniel Cohen-Or, Hui Huang | Disentangling visual layers in real-world images is a persistent challenge in vision and graphics, as such layers often involve non-linear and globally coupled interactions, including shading, reflection, and perspective distortion. In this work, we present an in-context image decomposition framework that leverages lar... | 2026/pdf/Gu_Cycle-Consistent_Tuning_for_Layered_Image_Decomposition_CVPR_2026_paper.pdf | @InProceedings{Gu_2026_CVPR,
author = {Gu, Zheng and Lu, Min and Sun, Zhida and Lischinski, Dani and Cohen-Or, Daniel and Huang, Hui},
title = {Cycle-Consistent Tuning for Layered Image Decomposition},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVP... | https://openaccess.thecvf.com/content/CVPR2026/papers/Gu_Cycle-Consistent_Tuning_for_Layered_Image_Decomposition_CVPR_2026_paper.pdf |
SketchVL: Policy Optimization via Fine-Grained Credit Assignment for Chart Understanding and More | Muye Huang, Lingling Zhang, Yifei Li, Yaqiang Wu, Jun Liu | Charts are high-density visual carriers of complex data and medium for information extraction and analysis. Due to the need for precise and complex visual reasoning, automated chart understanding poses a significant challenge to existing Multimodal Large Language Models (MLLMs). Many MLLMs trained with reinforcement le... | 2026/pdf/Huang_SketchVL_Policy_Optimization_via_Fine-Grained_Credit_Assignment_for_Chart_Understanding_CVPR_2026_paper.pdf | @InProceedings{Huang_2026_CVPR,
author = {Huang, Muye and Zhang, Lingling and Li, Yifei and Wu, Yaqiang and Liu, Jun},
title = {SketchVL: Policy Optimization via Fine-Grained Credit Assignment for Chart Understanding and More},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision an... | https://openaccess.thecvf.com/content/CVPR2026/papers/Huang_SketchVL_Policy_Optimization_via_Fine-Grained_Credit_Assignment_for_Chart_Understanding_CVPR_2026_paper.pdf |
ArchSym: Detecting 3D-Grounded Architectural Symmetries in the Wild | Hanyu Chen, Ruojin Cai, Steve Marschner, Noah Snavely | Symmetry detection is a fundamental problem in computer vision, and symmetries serve as powerful priors for downstream tasks. However, existing learning-based methods for detecting 3D symmetries from single images have been almost exclusively trained and evaluated on object-centric or synthetic datasets, and thus fail ... | 2026/pdf/Chen_ArchSym_Detecting_3D-Grounded_Architectural_Symmetries_in_the_Wild_CVPR_2026_paper.pdf | @InProceedings{Chen_2026_CVPR,
author = {Chen, Hanyu and Cai, Ruojin and Marschner, Steve and Snavely, Noah},
title = {ArchSym: Detecting 3D-Grounded Architectural Symmetries in the Wild},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
mont... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chen_ArchSym_Detecting_3D-Grounded_Architectural_Symmetries_in_the_Wild_CVPR_2026_paper.pdf |
Structural Graph Probing of Vision-Language Models | Haoyu He, Yue Zhuo, Yu Zheng, Qi R. Wang | Vision-language models (VLMs) achieve strong multimodal performance, yet how computation is organized across populations of neurons remains poorly understood. In this work, we study VLMs through the lens of neural topology, representing each layer as a within-layer correlation graph derived from neuron-neuron co-activa... | 2026/pdf/He_Structural_Graph_Probing_of_Vision-Language_Models_CVPR_2026_paper.pdf | @InProceedings{He_2026_CVPR,
author = {He, Haoyu and Zhuo, Yue and Zheng, Yu and Wang, Qi R.},
title = {Structural Graph Probing of Vision-Language Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = ... | https://openaccess.thecvf.com/content/CVPR2026/papers/He_Structural_Graph_Probing_of_Vision-Language_Models_CVPR_2026_paper.pdf |
P-Flow: Prompting Visual Effects Generation | Rui Zhao, Mike Zheng Shou | Recent advancements in video generation models have significantly improved their ability to follow text prompts. However, the customization of dynamic visual effects, defined as temporally evolving and appearance-driven visual phenomena like object crushing or explosion, remains underexplored. Prior works on motion cus... | 2026/pdf/Zhao_P-Flow_Prompting_Visual_Effects_Generation_CVPR_2026_paper.pdf | @InProceedings{Zhao_2026_CVPR,
author = {Zhao, Rui and Shou, Mike Zheng},
title = {P-Flow: Prompting Visual Effects Generation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2026},
pages = {914... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhao_P-Flow_Prompting_Visual_Effects_Generation_CVPR_2026_paper.pdf |
Teaching DINOv3 About Partial 3D Geometry: A Self-Supervised Geometry-Aware Approach | Viktoria Ehm, Dongliang Cao, Riccardo Marin, Daniel Scholz, Weikang Wang, Florian Bernard, Daniel Cremers | Partial shape matching is a crucial yet underexplored problem in 3D vision, with significant relevance to real-world scenarios where shapes are often only partially observed. Existing feature descriptors face difficulties in this setting, as traditional representations either struggle with the boundaries of partial sha... | 2026/pdf/Ehm_Teaching_DINOv3_About_Partial_3D_Geometry_A_Self-Supervised_Geometry-Aware_Approach_CVPR_2026_paper.pdf | @InProceedings{Ehm_2026_CVPR,
author = {Ehm, Viktoria and Cao, Dongliang and Marin, Riccardo and Scholz, Daniel and Wang, Weikang and Bernard, Florian and Cremers, Daniel},
title = {Teaching DINOv3 About Partial 3D Geometry: A Self-Supervised Geometry-Aware Approach},
booktitle = {Proceedings of the ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Ehm_Teaching_DINOv3_About_Partial_3D_Geometry_A_Self-Supervised_Geometry-Aware_Approach_CVPR_2026_paper.pdf |
One Token, Two Fates: A Unified Framework via Vision Token Manipulation Against MLLMs Hallucination | Zhan Fa, Yue Duan, Jian Zhang, Lei Qi, Yinghuan Shi | Current training-free methods tackle MLLM hallucination with separate strategies: either enhancing visual signals or suppressing text inertia. However, these separate methods are insufficient due to critical trade-offs: simply enhancing vision often fails against strong language prior, while suppressing language can in... | 2026/pdf/Fa_One_Token_Two_Fates_A_Unified_Framework_via_Vision_Token_CVPR_2026_paper.pdf | @InProceedings{Fa_2026_CVPR,
author = {Fa, Zhan and Duan, Yue and Zhang, Jian and Qi, Lei and Shi, Yinghuan},
title = {One Token, Two Fates: A Unified Framework via Vision Token Manipulation Against MLLMs Hallucination},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patte... | https://openaccess.thecvf.com/content/CVPR2026/papers/Fa_One_Token_Two_Fates_A_Unified_Framework_via_Vision_Token_CVPR_2026_paper.pdf |
SpatialDiff: 3D-Aware Object Movement via Implicit Spatial Modeling | Zheng Liu, Zijian He, Huiguo He, Weizhi Zhong, Yejun Tang, Huan Yang, Kun Gai, Guanbin Li | Recent advances in image editing allow impressive manipulation of objects, existing methods still struggle to handle spatial movement in complex scenes, such as objects span different depth layers or are partially occluded. Most image editing methods focus solely on prior information from 2D datasets, emphasizing plana... | 2026/pdf/Liu_SpatialDiff_3D-Aware_Object_Movement_via_Implicit_Spatial_Modeling_CVPR_2026_paper.pdf | @InProceedings{Liu_2026_CVPR,
author = {Liu, Zheng and He, Zijian and He, Huiguo and Zhong, Weizhi and Tang, Yejun and Yang, Huan and Gai, Kun and Li, Guanbin},
title = {SpatialDiff: 3D-Aware Object Movement via Implicit Spatial Modeling},
booktitle = {Proceedings of the IEEE/CVF Conference on Comput... | https://openaccess.thecvf.com/content/CVPR2026/papers/Liu_SpatialDiff_3D-Aware_Object_Movement_via_Implicit_Spatial_Modeling_CVPR_2026_paper.pdf |
Voxify3D: Pixel Art Meets Volumetric Rendering | Yi-Chuan Huang, Jiewen Chan, Hao-Jen Chien, Yu-Lun Liu | Voxel art is a distinctive stylization widely used in games and digital media, yet automated generation from 3D meshes remains challenging due to conflicting requirements of geometric abstraction, semantic preservation, and discrete color coherence. Existing methods either over-simplify geometry or fail to achieve the ... | 2026/pdf/Huang_Voxify3D_Pixel_Art_Meets_Volumetric_Rendering_CVPR_2026_paper.pdf | @InProceedings{Huang_2026_CVPR,
author = {Huang, Yi-Chuan and Chan, Jiewen and Chien, Hao-Jen and Liu, Yu-Lun},
title = {Voxify3D: Pixel Art Meets Volumetric Rendering},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Huang_Voxify3D_Pixel_Art_Meets_Volumetric_Rendering_CVPR_2026_paper.pdf |
Multi-modal Frequency Decomposition Network for Semantic Scene Completion | Die Zuo, Lubo Wang, Ruonan Liu, Qing Guo, Chong Wang, Dongdong Wu, Wei Feng, Kairui Yang, Di Lin | Based on an RGB-D image pair, semantic scene completion (SSC) provides a description for 3D scene understanding by predicting 3D semantic occupancy map. Recent methods extract RGB-D multi-modal features and fuse them in spatial domain, which disregards the misalignment caused by the imperfect raw multi-modal data and t... | 2026/pdf/Zuo_Multi-modal_Frequency_Decomposition_Network_for_Semantic_Scene_Completion_CVPR_2026_paper.pdf | @InProceedings{Zuo_2026_CVPR,
author = {Zuo, Die and Wang, Lubo and Liu, Ruonan and Guo, Qing and Wang, Chong and Wu, Dongdong and Feng, Wei and Yang, Kairui and Lin, Di},
title = {Multi-modal Frequency Decomposition Network for Semantic Scene Completion},
booktitle = {Proceedings of the IEEE/CVF Con... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zuo_Multi-modal_Frequency_Decomposition_Network_for_Semantic_Scene_Completion_CVPR_2026_paper.pdf |
GRPO-Guard: Mitigating Implicit Over-Optimization in Flow Matching via Regulated Clipping | Jing Wang, Jiajun Liang, Jie Liu, Henglin Liu, Gongye Liu, Jun Zheng, Wanyuan Pang, Ao Ma, Zhenyu Xie, Xintao Wang, Meng Wang, Pengfei Wan, Xiaodan Liang | Recently, GRPO-based reinforcement learning has shown remarkable progress in optimizing flow-matching models, effectively improving their alignment with task-specific rewards. Within these frameworks, the policy update relies on importance-ratio clipping to constrain overconfident positive and negative gradients. Howev... | 2026/pdf/Wang_GRPO-Guard_Mitigating_Implicit_Over-Optimization_in_Flow_Matching_via_Regulated_Clipping_CVPR_2026_paper.pdf | @InProceedings{Wang_2026_CVPR,
author = {Wang, Jing and Liang, Jiajun and Liu, Jie and Liu, Henglin and Liu, Gongye and Zheng, Jun and Pang, Wanyuan and Ma, Ao and Xie, Zhenyu and Wang, Xintao and Wang, Meng and Wan, Pengfei and Liang, Xiaodan},
title = {GRPO-Guard: Mitigating Implicit Over-Optimization ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wang_GRPO-Guard_Mitigating_Implicit_Over-Optimization_in_Flow_Matching_via_Regulated_Clipping_CVPR_2026_paper.pdf |
Beyond Missing Modalities: Hypergraph Conditioned Diffusion for Uncertainty-Aware Multimodal Emotion Recognition | Xihang Qiu, Yuhao Fang, Qing Zhou, Bin Zhai, Jialong Hong, Wanpeng Zhang, Yao Lu, Ye Zhang, Chun Li | Multimodal Emotion Recognition in Conversations (MERC) aims to understand emotions expressed in each utterance by effectively integrating audio, text, and visual modalities. However, in real-world scenarios, unavoidable missing modalities often degrade multimodal interpretation performance. To address this, we propose ... | 2026/pdf/Qiu_Beyond_Missing_Modalities_Hypergraph_Conditioned_Diffusion_for_Uncertainty-Aware_Multimodal_Emotion_CVPR_2026_paper.pdf | @InProceedings{Qiu_2026_CVPR,
author = {Qiu, Xihang and Fang, Yuhao and Zhou, Qing and Zhai, Bin and Hong, Jialong and Zhang, Wanpeng and Lu, Yao and Zhang, Ye and Li, Chun},
title = {Beyond Missing Modalities: Hypergraph Conditioned Diffusion for Uncertainty-Aware Multimodal Emotion Recognition},
bo... | https://openaccess.thecvf.com/content/CVPR2026/papers/Qiu_Beyond_Missing_Modalities_Hypergraph_Conditioned_Diffusion_for_Uncertainty-Aware_Multimodal_Emotion_CVPR_2026_paper.pdf |
Target-Aware Invertible Encoder with Reconstruction Guidance for Infrared Small Target Detection | Shule Yan, Zetian Zhang, Xiao Ma, Zexuan Ji | Modern detectors typically deepen backbones and rely on aggressive downsampling to harvest high-level semantics. But this severely degrades low-energy infrared tiny targets via rescale-induced information loss. This work introduces InvDet, a target-aware invertible encoder that unifies information preservation and targ... | 2026/pdf/Yan_Target-Aware_Invertible_Encoder_with_Reconstruction_Guidance_for_Infrared_Small_Target_CVPR_2026_paper.pdf | @InProceedings{Yan_2026_CVPR,
author = {Yan, Shule and Zhang, Zetian and Ma, Xiao and Ji, Zexuan},
title = {Target-Aware Invertible Encoder with Reconstruction Guidance for Infrared Small Target Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition... | https://openaccess.thecvf.com/content/CVPR2026/papers/Yan_Target-Aware_Invertible_Encoder_with_Reconstruction_Guidance_for_Infrared_Small_Target_CVPR_2026_paper.pdf |
Efficient Weighted Sampling via Score-based Generative Models | Heasung Kim, Taekyun Lee, Hyeji Kim, Gustavo De Veciana | Weighted sampling--sampling from a probability density function (PDF) proportional to the product of a base PDF and a weight function--is a fundamental technique with wide-ranging applications in variance reduction, biased sampling, data augmentation, and more. Leveraging the increasing availability of pretrained score... | 2026/pdf/Kim_Efficient_Weighted_Sampling_via_Score-based_Generative_Models_CVPR_2026_paper.pdf | @InProceedings{Kim_2026_CVPR,
author = {Kim, Heasung and Lee, Taekyun and Kim, Hyeji and De Veciana, Gustavo},
title = {Efficient Weighted Sampling via Score-based Generative Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kim_Efficient_Weighted_Sampling_via_Score-based_Generative_Models_CVPR_2026_paper.pdf |
Cross-View Distillation and Adaptive Masking for Incomplete Multi-View Multi-Label Classification | Yadong Liu, Qiaoqi Li, Yueying Wang, Lunke Fei, Jie Wen | While existing incomplete multi-view multi-label learning methods have achieved promising performance, few studies have focused on the issue of multi-view imbalance. Existing methods using gradient modulation or alternating optimization strategies alleviate this problem but often oversimplify the interaction between vi... | 2026/pdf/Liu_Cross-View_Distillation_and_Adaptive_Masking_for_Incomplete_Multi-View_Multi-Label_Classification_CVPR_2026_paper.pdf | @InProceedings{Liu_2026_CVPR,
author = {Liu, Yadong and Li, Qiaoqi and Wang, Yueying and Fei, Lunke and Wen, Jie},
title = {Cross-View Distillation and Adaptive Masking for Incomplete Multi-View Multi-Label Classification},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pa... | https://openaccess.thecvf.com/content/CVPR2026/papers/Liu_Cross-View_Distillation_and_Adaptive_Masking_for_Incomplete_Multi-View_Multi-Label_Classification_CVPR_2026_paper.pdf |
FastLightGen: Fast and Light Video Generation with Fewer Steps and Parameters | Shitong Shao, Yufei Gu, Zeke Xie | The recent advent of powerful video generation models, such as Hunyuan, WanX, Veo3, and Kling, has inaugurated a new era in the field. However, the practical deployment of these models is severely impeded by their substantial computational overhead, which stems from enormous parameter counts and the iterative, multi-st... | 2026/pdf/Shao_FastLightGen_Fast_and_Light_Video_Generation_with_Fewer_Steps_and_CVPR_2026_paper.pdf | @InProceedings{Shao_2026_CVPR,
author = {Shao, Shitong and Gu, Yufei and Xie, Zeke},
title = {FastLightGen: Fast and Light Video Generation with Fewer Steps and Parameters},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shao_FastLightGen_Fast_and_Light_Video_Generation_with_Fewer_Steps_and_CVPR_2026_paper.pdf |
SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation | Meihua Li, Yang Zhang, Weizhao He, Hu Qu, Yisong Li | Few-Shot Medical Image Segmentation (FSMIS) aims to segment novel object classes in medical images using only minimal annotated examples, addressing the critical challenges of data scarcity and domain shifts prevalent in medical imaging. While Diffusion Models (DM) excel in visual tasks, their potential for FSMIS remai... | 2026/pdf/Li_SD-FSMIS_Adapting_Stable_Diffusion_for_Few-Shot_Medical_Image_Segmentation_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Meihua and Zhang, Yang and He, Weizhao and Qu, Hu and Li, Yisong},
title = {SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_SD-FSMIS_Adapting_Stable_Diffusion_for_Few-Shot_Medical_Image_Segmentation_CVPR_2026_paper.pdf |
The Invisible Gorilla Effect in Out-of-distribution Detection | Harry Anthony, Ziyun Liang, Hermione Warr, Konstantinos Kamnitsas | Deep Neural Networks achieve high performance in vision tasks by learning features from regions of interest (ROI) within images, but their performance degrades when deployed on out-of-distribution (OOD) data that differs from training data. This challenge has led to OOD detection methods that aim to identify and reject... | 2026/pdf/Anthony_The_Invisible_Gorilla_Effect_in_Out-of-distribution_Detection_CVPR_2026_paper.pdf | @InProceedings{Anthony_2026_CVPR,
author = {Anthony, Harry and Liang, Ziyun and Warr, Hermione and Kamnitsas, Konstantinos},
title = {The Invisible Gorilla Effect in Out-of-distribution Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},... | https://openaccess.thecvf.com/content/CVPR2026/papers/Anthony_The_Invisible_Gorilla_Effect_in_Out-of-distribution_Detection_CVPR_2026_paper.pdf |
Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models | Chengsheng Zhang, Chenghao Sun, Xinyan Jiang, Wei Li, Xinmei Tian | Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual-textual understanding, yet their reliability is critically undermined by hallucinations, i.e., the generation of factually incorrect or inconsistent responses.While recent studies using steering vectors demonstrated promise in reducing hal... | 2026/pdf/Zhang_Prefill-Time_Intervention_for_Mitigating_Hallucination_in_Large_Vision-Language_Models_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Chengsheng and Sun, Chenghao and Jiang, Xinyan and Li, Wei and Tian, Xinmei},
title = {Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and P... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_Prefill-Time_Intervention_for_Mitigating_Hallucination_in_Large_Vision-Language_Models_CVPR_2026_paper.pdf |
Learning by Analogy: A Causal Framework for Compositional Generalization | Lingjing Kong, Shaoan Xie, Yang Jiao, Yetian Chen, Yanhui Guo, Simone Shao, Yan Gao, Guangyi Chen, Kun Zhang | Compositional generalization -- the ability to understand and generate novel combinations of learned concepts -- enables models to extend their capabilities beyond limited experiences. While effective, the data structures and principles that enable this crucial capability remain poorly understood. We propose that compo... | 2026/pdf/Kong_Learning_by_Analogy_A_Causal_Framework_for_Compositional_Generalization_CVPR_2026_paper.pdf | @InProceedings{Kong_2026_CVPR,
author = {Kong, Lingjing and Xie, Shaoan and Jiao, Yang and Chen, Yetian and Guo, Yanhui and Shao, Simone and Gao, Yan and Chen, Guangyi and Zhang, Kun},
title = {Learning by Analogy: A Causal Framework for Compositional Generalization},
booktitle = {Proceedings of the ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kong_Learning_by_Analogy_A_Causal_Framework_for_Compositional_Generalization_CVPR_2026_paper.pdf |
Rotation Invariant and Symmetry Aware Pixel Difference Network for Remote Sensing Object Detection | Jialei Zhan, Li Liu, Jiehua Zhang, Yuhang Xie, Yongxiang Liu, Jiangming Chen, Ming-Ming Cheng | Recent advancements in remote sensing object detection have predominantly focused on oriented bounding box design and small object feature enhancement, while often overlooking the intrinsic geometric properties of remote sensing images, such as rotation invariance and structural symmetry. Many aerial objects appear in ... | 2026/pdf/Zhan_Rotation_Invariant_and_Symmetry_Aware_Pixel_Difference_Network_for_Remote_CVPR_2026_paper.pdf | @InProceedings{Zhan_2026_CVPR,
author = {Zhan, Jialei and Liu, Li and Zhang, Jiehua and Xie, Yuhang and Liu, Yongxiang and Chen, Jiangming and Cheng, Ming-Ming},
title = {Rotation Invariant and Symmetry Aware Pixel Difference Network for Remote Sensing Object Detection},
booktitle = {Proceedings of t... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhan_Rotation_Invariant_and_Symmetry_Aware_Pixel_Difference_Network_for_Remote_CVPR_2026_paper.pdf |
UniPart: Part-Level 3D Generation with Unified 3D Geom-Seg Latents | Xufan He, Yushuang Wu, Xiaoyang Guo, Chongjie Ye, Jiaqing Zhou, Tianlei Hu, Xiaoguang Han, Dong Du | Part-level 3D generation is essential for applications requiring decomposable and structured 3D synthesis. However, existing methods either rely on implicit part segmentation with limited granularity control or depend on strong external segmenters trained on large annotated datasets. In this work, we observe that part ... | 2026/pdf/He_UniPart_Part-Level_3D_Generation_with_Unified_3D_Geom-Seg_Latents_CVPR_2026_paper.pdf | @InProceedings{He_2026_CVPR,
author = {He, Xufan and Wu, Yushuang and Guo, Xiaoyang and Ye, Chongjie and Zhou, Jiaqing and Hu, Tianlei and Han, Xiaoguang and Du, Dong},
title = {UniPart: Part-Level 3D Generation with Unified 3D Geom-Seg Latents},
booktitle = {Proceedings of the IEEE/CVF Conference on... | https://openaccess.thecvf.com/content/CVPR2026/papers/He_UniPart_Part-Level_3D_Generation_with_Unified_3D_Geom-Seg_Latents_CVPR_2026_paper.pdf |
Gamba: Mamba-based graph convolutional network with dynamic graph topology learning for action recognition | Rouyi Zhou, Yangzhi Wu, Jiajun Wen, Can Gao, Feng Liu, Zhihui Lai, Linlin Shen | Existing graph models predominantly utilize self-attention mechanisms to model feature correlations between the joints of each sample, which not only neglects dynamic relation dependencies in temporal dimension but also leads to redundant computation and difficulty in establishing a unified framework for joint relation... | 2026/pdf/Zhou_Gamba_Mamba-based_graph_convolutional_network_with_dynamic_graph_topology_learning_CVPR_2026_paper.pdf | @InProceedings{Zhou_2026_CVPR,
author = {Zhou, Rouyi and Wu, Yangzhi and Wen, Jiajun and Gao, Can and Liu, Feng and Lai, Zhihui and Shen, Linlin},
title = {Gamba: Mamba-based graph convolutional network with dynamic graph topology learning for action recognition},
booktitle = {Proceedings of the IEEE... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhou_Gamba_Mamba-based_graph_convolutional_network_with_dynamic_graph_topology_learning_CVPR_2026_paper.pdf |
Language-Guided One-Step Diffusion Model for Nighttime Flare Removal | Aoxiang Ning, Kailong Yu, Minglong Xue, Liyuan Pan, Jinhong He, Wenchao Yan, Mingliang Zhou, Yirui Wu | Nighttime photography is susceptible to flare caused by strong light sources, which degrades visual quality and disrupts structural information required by downstream vision tasks. Existing nighttime flare removal methods generally lack semantic priors for flare-occluded regions and thus tend to introduce artifacts and... | 2026/pdf/Ning_Language-Guided_One-Step_Diffusion_Model_for_Nighttime_Flare_Removal_CVPR_2026_paper.pdf | @InProceedings{Ning_2026_CVPR,
author = {Ning, Aoxiang and Yu, Kailong and Xue, Minglong and Pan, Liyuan and He, Jinhong and Yan, Wenchao and Zhou, Mingliang and Wu, Yirui},
title = {Language-Guided One-Step Diffusion Model for Nighttime Flare Removal},
booktitle = {Proceedings of the IEEE/CVF Confer... | https://openaccess.thecvf.com/content/CVPR2026/papers/Ning_Language-Guided_One-Step_Diffusion_Model_for_Nighttime_Flare_Removal_CVPR_2026_paper.pdf |
Instance-level Visual Active Tracking with Occlusion-Aware Planning | Haowei Sun, Kai Zhou, Hao Gao, Shiteng Zhang, Jinwu Hu, Xutao Wen, Qixiang Ye, Mingkui Tan | Visual Active Tracking (VAT) aims to control cameras to follow a target in 3D space, which is critical for applications like drone navigation and security surveillance. However, it faces two key bottlenecks in real-world deployment: confusion from visually similar distractors caused by insufficient instance-level discr... | 2026/pdf/Sun_Instance-level_Visual_Active_Tracking_with_Occlusion-Aware_Planning_CVPR_2026_paper.pdf | @InProceedings{Sun_2026_CVPR,
author = {Sun, Haowei and Zhou, Kai and Gao, Hao and Zhang, Shiteng and Hu, Jinwu and Wen, Xutao and Ye, Qixiang and Tan, Mingkui},
title = {Instance-level Visual Active Tracking with Occlusion-Aware Planning},
booktitle = {Proceedings of the IEEE/CVF Conference on Compu... | https://openaccess.thecvf.com/content/CVPR2026/papers/Sun_Instance-level_Visual_Active_Tracking_with_Occlusion-Aware_Planning_CVPR_2026_paper.pdf |
GeoDiff4D: Geometry-Aware Diffusion for 4D Head Avatar Reconstruction | Chao Xu, Xiaochen Zhao, Xiang Deng, Jingxiang Sun, Donglin Di, Zhuo Su, Yebin Liu | Reconstructing photorealistic and animatable 4D head avatars from a single portrait image remains a fundamental challenge in computer vision. While diffusion models have enabled remarkable progress in image and video generation for avatar reconstruction, existing methods primarily rely on 2D priors and struggle to achi... | 2026/pdf/Xu_GeoDiff4D_Geometry-Aware_Diffusion_for_4D_Head_Avatar_Reconstruction_CVPR_2026_paper.pdf | @InProceedings{Xu_2026_CVPR,
author = {Xu, Chao and Zhao, Xiaochen and Deng, Xiang and Sun, Jingxiang and Di, Donglin and Su, Zhuo and Liu, Yebin},
title = {GeoDiff4D: Geometry-Aware Diffusion for 4D Head Avatar Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision a... | https://openaccess.thecvf.com/content/CVPR2026/papers/Xu_GeoDiff4D_Geometry-Aware_Diffusion_for_4D_Head_Avatar_Reconstruction_CVPR_2026_paper.pdf |
HandX: Scaling Bimanual Motion and Interaction Generation | Zimu Zhang, Yucheng Zhang, Xiyan Xu, Ziyin Wang, Sirui Xu, Kai Zhou, Bing Zhou, Chuan Guo, Jian Wang, Yu-Xiong Wang, Liang-Yan Gui | Synthesizing human motion has advanced rapidly, yet realistic hand motion and bimanual interaction remain underexplored. Whole-body models often miss the fine-grained cues that drive dexterous behavior, finger articulation, contact timing, and inter-hand coordination, and existing resources lack high-fidelity bimanual ... | 2026/pdf/Zhang_HandX_Scaling_Bimanual_Motion_and_Interaction_Generation_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Zimu and Zhang, Yucheng and Xu, Xiyan and Wang, Ziyin and Xu, Sirui and Zhou, Kai and Zhou, Bing and Guo, Chuan and Wang, Jian and Wang, Yu-Xiong and Gui, Liang-Yan},
title = {HandX: Scaling Bimanual Motion and Interaction Generation},
booktitle = {Pro... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_HandX_Scaling_Bimanual_Motion_and_Interaction_Generation_CVPR_2026_paper.pdf |
LLaVAShield: Safeguarding Multimodal Multi-Turn Dialogues in Vision-Language Models | Guolei Huang, Qinzhi Peng, Gan Xu, Yao Huang, Yuxuan Lu, Yongjun Shen | As Vision-Language Models (VLMs) move into interactive, multi-turn use, safety concerns intensify for multimodal multi-turn dialogue, which is characterized by concealment of malicious intent, contextual risk accumulation, and cross-modal joint risk. These characteristics limit the effectiveness of content moderation a... | 2026/pdf/Huang_LLaVAShield_Safeguarding_Multimodal_Multi-Turn_Dialogues_in_Vision-Language_Models_CVPR_2026_paper.pdf | @InProceedings{Huang_2026_CVPR,
author = {Huang, Guolei and Peng, Qinzhi and Xu, Gan and Huang, Yao and Lu, Yuxuan and Shen, Yongjun},
title = {LLaVAShield: Safeguarding Multimodal Multi-Turn Dialogues in Vision-Language Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Huang_LLaVAShield_Safeguarding_Multimodal_Multi-Turn_Dialogues_in_Vision-Language_Models_CVPR_2026_paper.pdf |
R2G: A Multi-View Circuit Graph Benchmark Suite from RTL to GDSII | Zewei Zhou, Jiajun Zou, Jiajia Zhang, Ao Yang, Ruichao He, Haozheng Zhou, Ao Liu, Jiawei Liu, Leilei Jin, Shan Shen, Daying Sun | Graph neural networks (GNNs) are increasingly applied to physical design tasks such as congestion prediction and wirelength estimation, yet progress is hindered by inconsistent circuit representations and the absence of controlled evaluation protocols. We present R2G (RTL-to-GDSII), a multi-view circuit-graph benchmark... | 2026/pdf/Zhou_R2G_A_Multi-View_Circuit_Graph_Benchmark_Suite_from_RTL_to_CVPR_2026_paper.pdf | @InProceedings{Zhou_2026_CVPR,
author = {Zhou, Zewei and Zou, Jiajun and Zhang, Jiajia and Yang, Ao and He, Ruichao and Zhou, Haozheng and Liu, Ao and Liu, Jiawei and Jin, Leilei and Shen, Shan and Sun, Daying},
title = {R2G: A Multi-View Circuit Graph Benchmark Suite from RTL to GDSII},
booktitle = ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhou_R2G_A_Multi-View_Circuit_Graph_Benchmark_Suite_from_RTL_to_CVPR_2026_paper.pdf |
Time-Specialized Event-Image Alignment for Blur-to-Video Decomposition | Zhijing Sun, Senyan Xu, Ruixuan Jiang, Kean Liu, Runze Tian, Xueyang Fu, Zheng-Jun Zha | Motion blur is a common degradation in dynamic imaging. Recent studies have moved beyond restoring a single sharp image from a blurred input and instead target blur decomposition: recovering a temporally continuous sharp video sequence from one motion-blurred image. Event cameras, with their microsecond temporal resolu... | 2026/pdf/Sun_Time-Specialized_Event-Image_Alignment_for_Blur-to-Video_Decomposition_CVPR_2026_paper.pdf | @InProceedings{Sun_2026_CVPR,
author = {Sun, Zhijing and Xu, Senyan and Jiang, Ruixuan and Liu, Kean and Tian, Runze and Fu, Xueyang and Zha, Zheng-Jun},
title = {Time-Specialized Event-Image Alignment for Blur-to-Video Decomposition},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer V... | https://openaccess.thecvf.com/content/CVPR2026/papers/Sun_Time-Specialized_Event-Image_Alignment_for_Blur-to-Video_Decomposition_CVPR_2026_paper.pdf |
JUMP-Hand: Learning Joint-wise Uncertainty to Gate Mixture of View Experts for Multi-View 3D Hand Reconstruction | Haohong Kuang, Yang Xiao, Changlong Jiang, Jinghong Zheng, Hang Xu, Ran Wang, Zhiguo Cao, Joey Tianyi Zhou | We propose JUMP-Hand, a novel multi-view 3D hand reconstruction method that explicitly models probabilistic joint-wise uncertainty as a gating mechanism for multi-view fusion. Existing approaches usually rely on naive pooling or implicit attention, overlooking that each hand joint exhibits varying visibility and reliab... | 2026/pdf/Kuang_JUMP-Hand_Learning_Joint-wise_Uncertainty_to_Gate_Mixture_of_View_Experts_CVPR_2026_paper.pdf | @InProceedings{Kuang_2026_CVPR,
author = {Kuang, Haohong and Xiao, Yang and Jiang, Changlong and Zheng, Jinghong and Xu, Hang and Wang, Ran and Cao, Zhiguo and Zhou, Joey Tianyi},
title = {JUMP-Hand: Learning Joint-wise Uncertainty to Gate Mixture of View Experts for Multi-View 3D Hand Reconstruction},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kuang_JUMP-Hand_Learning_Joint-wise_Uncertainty_to_Gate_Mixture_of_View_Experts_CVPR_2026_paper.pdf |
From Manuals to Actions: A Unified VLA Model for Chain-of-Thought Manual Generation and Robotic Manipulation | Chenyang Gu, Jiaming Liu, Hao Chen, Runzhong Huang, Qingpo Wuwu, Xiaoqi Li, Zhuoyang Liu, Ying Li, Renrui Zhang, Peng Jia, Pheng-Ann Heng, Shanghang Zhang | Vision-Language-Action (VLA) models have recently emerged, demonstrating strong generalization in robotic scene understanding and manipulation. However, when confronted with long-horizon tasks that require defined goal states, such as LEGO assembly or object rearrangement, existing VLA models still face challenges in c... | 2026/pdf/Gu_From_Manuals_to_Actions_A_Unified_VLA_Model_for_Chain-of-Thought_CVPR_2026_paper.pdf | @InProceedings{Gu_2026_CVPR,
author = {Gu, Chenyang and Liu, Jiaming and Chen, Hao and Huang, Runzhong and Wuwu, Qingpo and Li, Xiaoqi and Liu, Zhuoyang and Li, Ying and Zhang, Renrui and Jia, Peng and Heng, Pheng-Ann and Zhang, Shanghang},
title = {From Manuals to Actions: A Unified VLA Model for Chain-... | https://openaccess.thecvf.com/content/CVPR2026/papers/Gu_From_Manuals_to_Actions_A_Unified_VLA_Model_for_Chain-of-Thought_CVPR_2026_paper.pdf |
Anatomical Domain Shifts: Test-time Heterogeneous Adaptation for 3D Human Pose Prediction | Qiongjie Cui, Pan Zhou, Jingjing Chen, Na Zhao | The research frontier in human pose prediction (HPP) is advancing toward continual test-time adaptation (TTA), where models must self-adapt to dynamic test distributions. To date, the homeostatic continual TTA remains the sole viable solution, which isolates the model parameters and update domain-sensitive ones. Despit... | 2026/pdf/Cui_Anatomical_Domain_Shifts_Test-time_Heterogeneous_Adaptation_for_3D_Human_Pose_CVPR_2026_paper.pdf | @InProceedings{Cui_2026_CVPR,
author = {Cui, Qiongjie and Zhou, Pan and Chen, Jingjing and Zhao, Na},
title = {Anatomical Domain Shifts: Test-time Heterogeneous Adaptation for 3D Human Pose Prediction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CV... | https://openaccess.thecvf.com/content/CVPR2026/papers/Cui_Anatomical_Domain_Shifts_Test-time_Heterogeneous_Adaptation_for_3D_Human_Pose_CVPR_2026_paper.pdf |
Pointing at Parts: Training-Free Few-Shot Grounding in Multimodal LLMs | Shiang-Feng Tsai, Yuan-Hong Liao, Jin-Cheng Jhang, Nan Qiao, Min Sun | Part-level pointing is important for fine-grained interaction and reasoning, yet existing Multimodal Large Language Models (MLLMs) remain limited to instance-level pointing. Part-level pointing presents unique challenges: annotation is costly, parts are long-tail distributed, and many are difficult to specify precisely... | 2026/pdf/Tsai_Pointing_at_Parts_Training-Free_Few-Shot_Grounding_in_Multimodal_LLMs_CVPR_2026_paper.pdf | @InProceedings{Tsai_2026_CVPR,
author = {Tsai, Shiang-Feng and Liao, Yuan-Hong and Jhang, Jin-Cheng and Qiao, Nan and Sun, Min},
title = {Pointing at Parts: Training-Free Few-Shot Grounding in Multimodal LLMs},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni... | https://openaccess.thecvf.com/content/CVPR2026/papers/Tsai_Pointing_at_Parts_Training-Free_Few-Shot_Grounding_in_Multimodal_LLMs_CVPR_2026_paper.pdf |
SubspaceAD: Training-Free Few-Shot Anomaly Detection via Subspace Modeling | Camile Lendering, Erkut Akdag, Egor Bondarau | Detecting visual anomalies in industrial inspection often requires training with only a few normal images per category. Recent few-shot methods achieve strong results employing foundation-model features, but typically rely on memory banks, auxiliary datasets, or multi-modal tuning of vision-language models. We therefor... | 2026/pdf/Lendering_SubspaceAD_Training-Free_Few-Shot_Anomaly_Detection_via_Subspace_Modeling_CVPR_2026_paper.pdf | @InProceedings{Lendering_2026_CVPR,
author = {Lendering, Camile and Akdag, Erkut and Bondarau, Egor},
title = {SubspaceAD: Training-Free Few-Shot Anomaly Detection via Subspace Modeling},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month... | https://openaccess.thecvf.com/content/CVPR2026/papers/Lendering_SubspaceAD_Training-Free_Few-Shot_Anomaly_Detection_via_Subspace_Modeling_CVPR_2026_paper.pdf |
Evolving Contextual Safety in Multi-Modal Large Language Models via Inference-Time Self-Reflective Memory | Ce Zhang, Jinxi He, Junyi He, Katia Sycara, Yaqi Xie | Multi-modal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of visual reasoning tasks, yet their vulnerability to safety risks remains a pressing concern. While prior research primarily focuses on jailbreak defenses that detect and refuse explicitly unsafe inputs, such approaches ... | 2026/pdf/Zhang_Evolving_Contextual_Safety_in_Multi-Modal_Large_Language_Models_via_Inference-Time_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Ce and He, Jinxi and He, Junyi and Sycara, Katia and Xie, Yaqi},
title = {Evolving Contextual Safety in Multi-Modal Large Language Models via Inference-Time Self-Reflective Memory},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_Evolving_Contextual_Safety_in_Multi-Modal_Large_Language_Models_via_Inference-Time_CVPR_2026_paper.pdf |
FlashMesh: Faster and Better Autoregressive Mesh Synthesis via Structured Speculation | Tingrui Shen, Yiheng Zhang, Chen Tang, Chuan Ping, Zixing Zhao, Le Wan, Yuwang Wang, Ronggang Wang, Shengfeng He | Autoregressive models can generate high-quality 3D meshes by sequentially producing vertices and faces, but their token-by-token decoding results in slow inference, limiting practical use in interactive and large-scale applications.We present FlashMesh, a fast and high-fidelity mesh generation framework that rethinks a... | 2026/pdf/Shen_FlashMesh_Faster_and_Better_Autoregressive_Mesh_Synthesis_via_Structured_Speculation_CVPR_2026_paper.pdf | @InProceedings{Shen_2026_CVPR,
author = {Shen, Tingrui and Zhang, Yiheng and Tang, Chen and Ping, Chuan and Zhao, Zixing and Wan, Le and Wang, Yuwang and Wang, Ronggang and He, Shengfeng},
title = {FlashMesh: Faster and Better Autoregressive Mesh Synthesis via Structured Speculation},
booktitle = {Pr... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shen_FlashMesh_Faster_and_Better_Autoregressive_Mesh_Synthesis_via_Structured_Speculation_CVPR_2026_paper.pdf |
SeeThrough3D: Occlusion Aware 3D Control in Text-to-Image Generation | Vaibhav Agrawal, Rishubh Parihar, Pradhaan S Bhat, Ravi Kiran Sarvadevabhatla, Venkatesh Babu Radhakrishnan | We identify occlusion reasoning as a fundamental yet overlooked aspect for 3D layout-conditioned generation. It is essential for synthesizing partially occluded objects with depth-consistent geometry and scale. While existing methods can generate realistic scenes that follow input layouts, they often fail to model prec... | 2026/pdf/Agrawal_SeeThrough3D_Occlusion_Aware_3D_Control_in_Text-to-Image_Generation_CVPR_2026_paper.pdf | @InProceedings{Agrawal_2026_CVPR,
author = {Agrawal, Vaibhav and Parihar, Rishubh and Bhat, Pradhaan S and Sarvadevabhatla, Ravi Kiran and Radhakrishnan, Venkatesh Babu},
title = {SeeThrough3D: Occlusion Aware 3D Control in Text-to-Image Generation},
booktitle = {Proceedings of the IEEE/CVF Conferenc... | https://openaccess.thecvf.com/content/CVPR2026/papers/Agrawal_SeeThrough3D_Occlusion_Aware_3D_Control_in_Text-to-Image_Generation_CVPR_2026_paper.pdf |
RARE: Learn to RAnk and REtrieve for Monocular 3D Object Detection | Hyeonjeong Park, Peixi Xiong, Xiaoqian Ruan, Dian Jia, Pei Yu, Wei Tang | Monocular 3D object detection from a single RGB image remains challenging due to two fundamental challenges: the ill-posed nature of 3D localization, where multiple plausible configurations can correspond to the same 2D observation, and unreliable confidence estimation that fails to reflect true localization accuracy. ... | 2026/pdf/Park_RARE_Learn_to_RAnk_and_REtrieve_for_Monocular_3D_Object_CVPR_2026_paper.pdf | @InProceedings{Park_2026_CVPR,
author = {Park, Hyeonjeong and Xiong, Peixi and Ruan, Xiaoqian and Jia, Dian and Yu, Pei and Tang, Wei},
title = {RARE: Learn to RAnk and REtrieve for Monocular 3D Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Reco... | https://openaccess.thecvf.com/content/CVPR2026/papers/Park_RARE_Learn_to_RAnk_and_REtrieve_for_Monocular_3D_Object_CVPR_2026_paper.pdf |
Exemplar-Free Class Incremental Learning via Preserving Class-Discriminative Structure | Xin Zhang, Liang Bai, Guanchao Wang, Xian Yang | Exemplar-Free Class Incremental Learning (EFCIL) aims to enable models to learn new classes sequentially without retaining samples from previous tasks. While recent approaches leverage pre-trained models with parameter-efficient tuning to mitigate forgetting, they often overlook a crucial cause of forgetting: the colla... | 2026/pdf/Zhang_Exemplar-Free_Class_Incremental_Learning_via_Preserving_Class-Discriminative_Structure_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Xin and Bai, Liang and Wang, Guanchao and Yang, Xian},
title = {Exemplar-Free Class Incremental Learning via Preserving Class-Discriminative Structure},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVP... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_Exemplar-Free_Class_Incremental_Learning_via_Preserving_Class-Discriminative_Structure_CVPR_2026_paper.pdf |
3D Gaussian Splatting with Self-Constrained Priors for High Fidelity Surface Reconstruction | Takeshi Noda, Yu-Shen Liu, Zhizhong Han | Rendering 3D surfaces has been revolutionized within the modeling of radiance fields through either 3DGS or NeRF. Although 3DGS has shown advantages over NeRF in terms of rendering quality or speed, there is still room for improvement in recovering high fidelity surfaces through 3DGS. To resolve this issue, we propose ... | 2026/pdf/Noda_3D_Gaussian_Splatting_with_Self-Constrained_Priors_for_High_Fidelity_Surface_CVPR_2026_paper.pdf | @InProceedings{Noda_2026_CVPR,
author = {Noda, Takeshi and Liu, Yu-Shen and Han, Zhizhong},
title = {3D Gaussian Splatting with Self-Constrained Priors for High Fidelity Surface Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Noda_3D_Gaussian_Splatting_with_Self-Constrained_Priors_for_High_Fidelity_Surface_CVPR_2026_paper.pdf |
Do You See What I Am Pointing At? Gesture-Based Egocentric Video Question Answering | Yura Choi, Roy Miles, Rolandos Alexandros Potamias, Ismail Elezi, Jiankang Deng, Stefanos Zafeiriou | Understanding and answering questions based on a user's pointing gesture is essential for next-generation egocentric AI assistants. However, current Multimodal Large Language Models (MLLMs) struggle with such tasks due to the lack of gesture-rich data and their limited ability to infer fine-grained pointing intent from... | 2026/pdf/Choi_Do_You_See_What_I_Am_Pointing_At_Gesture-Based_Egocentric_CVPR_2026_paper.pdf | @InProceedings{Choi_2026_CVPR,
author = {Choi, Yura and Miles, Roy and Potamias, Rolandos Alexandros and Elezi, Ismail and Deng, Jiankang and Zafeiriou, Stefanos},
title = {Do You See What I Am Pointing At? Gesture-Based Egocentric Video Question Answering},
booktitle = {Proceedings of the IEEE/CVF C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Choi_Do_You_See_What_I_Am_Pointing_At_Gesture-Based_Egocentric_CVPR_2026_paper.pdf |
VideoSSR: Video Self-Supervised Reinforcement Learning | Zefeng He, Xiaoye Qu, Yafu Li, Siyuan Huang, Daizong Liu, Yu Cheng | Reinforcement Learning with Verifiable Reward (RLVR) has substantially advanced the video understanding capabilities of Multimodal Large Language Models (MLLMs). However, the rapid progress of MLLMs is outpacing the complexity of existing video datasets, while the manual annotation of new, high-quality data remains pro... | 2026/pdf/He_VideoSSR_Video_Self-Supervised_Reinforcement_Learning_CVPR_2026_paper.pdf | @InProceedings{He_2026_CVPR,
author = {He, Zefeng and Qu, Xiaoye and Li, Yafu and Huang, Siyuan and Liu, Daizong and Cheng, Yu},
title = {VideoSSR: Video Self-Supervised Reinforcement Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/He_VideoSSR_Video_Self-Supervised_Reinforcement_Learning_CVPR_2026_paper.pdf |
Disentangling to Re-couple: Resolving the Similarity-Controllability Paradox in Subject-Driven Text-to-Image Generation | Shuang Li, Chao Deng, Hang Chen, Liqun Liu, Zhenyu Hu, Te Cao, Mengge Xue, Yuan Chen, Peng Shu, Huan Yu, Jie Jiang | Subject-Driven Text-to-Image (T2I) Generation aims to preserve a subject's identity while editing its context based on a text prompt. A core challenge in this task is the "similarity-controllability paradox", where enhancing textual control often degrades the subject's fidelity, and vice-versa. We argue this paradox st... | 2026/pdf/Li_Disentangling_to_Re-couple_Resolving_the_Similarity-Controllability_Paradox_in_Subject-Driven_Text-to-Image_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Shuang and Deng, Chao and Chen, Hang and Liu, Liqun and Hu, Zhenyu and Cao, Te and Xue, Mengge and Chen, Yuan and Shu, Peng and Yu, Huan and Jiang, Jie},
title = {Disentangling to Re-couple: Resolving the Similarity-Controllability Paradox in Subject-Driven Text... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_Disentangling_to_Re-couple_Resolving_the_Similarity-Controllability_Paradox_in_Subject-Driven_Text-to-Image_CVPR_2026_paper.pdf |
Reasoning Diffusion for Unpaired Test Time Out-of-distribution Text-Image to Video Generation | Zirui Pan, Xin Wang, Yipeng Zhang, Hong Chen, Kecheng Zheng, Wenwu Zhu | Text-image to video generation aims to synthesize a video conditioned on the given text-image inputs. Nevertheless, existing methods generally assume that the semantic information carried in the input text and image tends to be perfectly paired and temporally aligned, occurring simultaneously in the generated video. As... | 2026/pdf/Pan_Reasoning_Diffusion_for_Unpaired_Test_Time_Out-of-distribution_Text-Image_to_Video_CVPR_2026_paper.pdf | @InProceedings{Pan_2026_CVPR,
author = {Pan, Zirui and Wang, Xin and Zhang, Yipeng and Chen, Hong and Zheng, Kecheng and Zhu, Wenwu},
title = {Reasoning Diffusion for Unpaired Test Time Out-of-distribution Text-Image to Video Generation},
booktitle = {Proceedings of the IEEE/CVF Conference on Compute... | https://openaccess.thecvf.com/content/CVPR2026/papers/Pan_Reasoning_Diffusion_for_Unpaired_Test_Time_Out-of-distribution_Text-Image_to_Video_CVPR_2026_paper.pdf |
Generalizing Visual Geometry Priors to Sparse Gaussian Occupancy Prediction | Changqing Zhou, Yueru Luo, Changhao Chen | Accurate 3D scene understanding is essential for embodied intelligence, with occupancy prediction emerging as a key task for reasoning about both objects and free space. Existing approaches largely rely on depth priors (e.g., DepthAnything) but make only limited use of 3D cues, restricting performance and generalizatio... | 2026/pdf/Zhou_Generalizing_Visual_Geometry_Priors_to_Sparse_Gaussian_Occupancy_Prediction_CVPR_2026_paper.pdf | @InProceedings{Zhou_2026_CVPR,
author = {Zhou, Changqing and Luo, Yueru and Chen, Changhao},
title = {Generalizing Visual Geometry Priors to Sparse Gaussian Occupancy Prediction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhou_Generalizing_Visual_Geometry_Priors_to_Sparse_Gaussian_Occupancy_Prediction_CVPR_2026_paper.pdf |
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