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 |
|---|---|---|---|---|---|
Efficient Training for Human Video Generation with Entropy-Guided Prioritized Progressive Learning | Changlin Li, Jiawei Zhang, Shuhao Liu, Sihao Lin, Zeyi Shi, Zhihui Li, Xiaojun Chang | Human video generation has advanced rapidly with the development of diffusion models, but the high computational cost and substantial memory consumption associated with training these models on high-resolution, multi-frame data pose significant challenges. In this paper, we propose Entropy-Guided Prioritized Progressiv... | 2026/pdf/Li_Efficient_Training_for_Human_Video_Generation_with_Entropy-Guided_Prioritized_Progressive_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Changlin and Zhang, Jiawei and Liu, Shuhao and Lin, Sihao and Shi, Zeyi and Li, Zhihui and Chang, Xiaojun},
title = {Efficient Training for Human Video Generation with Entropy-Guided Prioritized Progressive Learning},
booktitle = {Proceedings of the IEEE/CVF... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_Efficient_Training_for_Human_Video_Generation_with_Entropy-Guided_Prioritized_Progressive_CVPR_2026_paper.pdf |
MFEN: Multi-Frequency Expert Network for Visible-Infrared Person Re-ID | Xulin Li, Yan Lu, Bin Liu, Qinhong Yang, Qi Chu, Tao Gong, Nenghai Yu | Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. We contend that this discrepancy is largely related to differing lighting conditions, including differences in light wavelength and light source type. Recently, frequency-based V... | 2026/pdf/Li_MFEN_Multi-Frequency_Expert_Network_for_Visible-Infrared_Person_Re-ID_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Xulin and Lu, Yan and Liu, Bin and Yang, Qinhong and Chu, Qi and Gong, Tao and Yu, Nenghai},
title = {MFEN: Multi-Frequency Expert Network for Visible-Infrared Person Re-ID},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_MFEN_Multi-Frequency_Expert_Network_for_Visible-Infrared_Person_Re-ID_CVPR_2026_paper.pdf |
CoT-Edit: Let CoT Guide Instruction Video Editing | Sen Liang, Fengbin Guan, Youliang Zhang, Xin Li, Zhibo Chen | Text-driven instruction-based video editing in complex scenes remains challenging: purely textual prompts often fail to capture precise spatial relationships and physical constraints, resulting in target ambiguity and physically implausible outcomes. To address this, we propose a plan-guide-edit framework that explicit... | 2026/pdf/Liang_CoT-Edit_Let_CoT_Guide_Instruction_Video_Editing_CVPR_2026_paper.pdf | @InProceedings{Liang_2026_CVPR,
author = {Liang, Sen and Guan, Fengbin and Zhang, Youliang and Li, Xin and Chen, Zhibo},
title = {CoT-Edit: Let CoT Guide Instruction Video Editing},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month =... | https://openaccess.thecvf.com/content/CVPR2026/papers/Liang_CoT-Edit_Let_CoT_Guide_Instruction_Video_Editing_CVPR_2026_paper.pdf |
Sparse Spectral LoRA: Routed Experts for Medical VLMs | Omid Nejatimanzari, Hojat Asgariandehkordi, Taha Koleilat, Yiming Xiao, Hassan Rivaz | Large vision-language models (VLMs) excel on general benchmarks but often lack robustness in medical imaging, where heterogeneous supervision induces cross-dataset interference and sensitivity to data regime (i.e., how the supervisory signals are mixed). In realistic clinical workflows, data and tasks arrive sequential... | 2026/pdf/Nejatimanzari_Sparse_Spectral_LoRA_Routed_Experts_for_Medical_VLMs_CVPR_2026_paper.pdf | @InProceedings{Nejatimanzari_2026_CVPR,
author = {Nejatimanzari, Omid and Asgariandehkordi, Hojat and Koleilat, Taha and Xiao, Yiming and Rivaz, Hassan},
title = {Sparse Spectral LoRA: Routed Experts for Medical VLMs},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern... | https://openaccess.thecvf.com/content/CVPR2026/papers/Nejatimanzari_Sparse_Spectral_LoRA_Routed_Experts_for_Medical_VLMs_CVPR_2026_paper.pdf |
From Softmax to Dirichlet: Evidential Learning for Semi-supervised Semantic Segmentation | Huayu Mai, Rui Sun, Yujia Chen, Wangkai Li, Bingzhou Wang, Aibing Li, Zhangyu He, Yuan Wang | The critical challenge of semi-supervised semantic segmentation lies in how to fully exploit a large volume of unlabeled data to improve the model's generalization performance for robust segmentation. However, existing softmax scores-based filtering methods tend to be affected by the overconfidence issue in neural netw... | 2026/pdf/Mai_From_Softmax_to_Dirichlet_Evidential_Learning_for_Semi-supervised_Semantic_Segmentation_CVPR_2026_paper.pdf | @InProceedings{Mai_2026_CVPR,
author = {Mai, Huayu and Sun, Rui and Chen, Yujia and Li, Wangkai and Wang, Bingzhou and Li, Aibing and He, Zhangyu and Wang, Yuan},
title = {From Softmax to Dirichlet: Evidential Learning for Semi-supervised Semantic Segmentation},
booktitle = {Proceedings of the IEEE/C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Mai_From_Softmax_to_Dirichlet_Evidential_Learning_for_Semi-supervised_Semantic_Segmentation_CVPR_2026_paper.pdf |
DiT-IC: Aligned Diffusion Transformer for Efficient Image Compression | Junqi Shi, Ming Lu, Xingchen Li, Anle Ke, Ruiqi Zhang, Zhan Ma | Diffusion-based image compression has recently shown outstanding perceptual fidelity, yet its practicality is hindered by prohibitive sampling overhead and high memory usage.Most existing diffusion codecs employ UNet architectures, where hierarchical downsampling forces diffusion to operate in shallow latent spaces (ty... | 2026/pdf/Shi_DiT-IC_Aligned_Diffusion_Transformer_for_Efficient_Image_Compression_CVPR_2026_paper.pdf | @InProceedings{Shi_2026_CVPR,
author = {Shi, Junqi and Lu, Ming and Li, Xingchen and Ke, Anle and Zhang, Ruiqi and Ma, Zhan},
title = {DiT-IC: Aligned Diffusion Transformer for Efficient Image Compression},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition... | https://openaccess.thecvf.com/content/CVPR2026/papers/Shi_DiT-IC_Aligned_Diffusion_Transformer_for_Efficient_Image_Compression_CVPR_2026_paper.pdf |
Principled Steering via Null-space Projection for Jailbreak Defense in Vision-Language Models | Xingyu Zhu, Beier Zhu, Shuo Wang, Junfeng Fang, Kesen Zhao, Hanwang Zhang, Xiangnan He | As vision-language models (VLMs) are increasingly deployed in open-world scenarios, they can be easily induced by visual jailbreak attacks to generate harmful content, posing serious risks to model safety and trustworthy usage.Recent activation steering methods inject directional vectors into model activations during i... | 2026/pdf/Zhu_Principled_Steering_via_Null-space_Projection_for_Jailbreak_Defense_in_Vision-Language_CVPR_2026_paper.pdf | @InProceedings{Zhu_2026_CVPR,
author = {Zhu, Xingyu and Zhu, Beier and Wang, Shuo and Fang, Junfeng and Zhao, Kesen and Zhang, Hanwang and He, Xiangnan},
title = {Principled Steering via Null-space Projection for Jailbreak Defense in Vision-Language Models},
booktitle = {Proceedings of the IEEE/CVF C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhu_Principled_Steering_via_Null-space_Projection_for_Jailbreak_Defense_in_Vision-Language_CVPR_2026_paper.pdf |
FlowDirector: Training-Free Flow Steering for Precise Text-to-Video Editing | Guangzhao Li, Yanming Yang, Chenxi Song, Xiaohong Liu, Chi Zhang | Text-driven video editing aims to modify video content based on natural language instructions. While recent training-free methods have leveraged pretrained diffusion models, they often rely on an inversion-editing paradigm. This paradigm maps the video to a latent space before editing. However, the inversion process is... | 2026/pdf/Li_FlowDirector_Training-Free_Flow_Steering_for_Precise_Text-to-Video_Editing_CVPR_2026_paper.pdf | @InProceedings{Li_2026_CVPR,
author = {Li, Guangzhao and Yang, Yanming and Song, Chenxi and Liu, Xiaohong and Zhang, Chi},
title = {FlowDirector: Training-Free Flow Steering for Precise Text-to-Video Editing},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognit... | https://openaccess.thecvf.com/content/CVPR2026/papers/Li_FlowDirector_Training-Free_Flow_Steering_for_Precise_Text-to-Video_Editing_CVPR_2026_paper.pdf |
ImageRAGTurbo: Towards One-step Text-to-Image Generation with Retrieval-Augmented Diffusion Models | Peijie Qiu, Hariharan Ramshankar, Arnau Ramisa, Amit Kumar K C, René Vidal, Vamsi Salaka, Rahul Bhagat | Diffusion models have emerged as the leading approach for text-to-image generation. However, their iterative sampling process, which gradually morphs random noise into coherent images, introduces significant latency that limits their applicability. While recent few-step diffusion models reduce the number of sampling st... | 2026/pdf/Qiu_ImageRAGTurbo_Towards_One-step_Text-to-Image_Generation_with_Retrieval-Augmented_Diffusion_Models_CVPR_2026_paper.pdf | @InProceedings{Qiu_2026_CVPR,
author = {Qiu, Peijie and Ramshankar, Hariharan and Ramisa, Arnau and C, Amit Kumar K and Vidal, Ren\'e and Salaka, Vamsi and Bhagat, Rahul},
title = {ImageRAGTurbo: Towards One-step Text-to-Image Generation with Retrieval-Augmented Diffusion Models},
booktitle = {Procee... | https://openaccess.thecvf.com/content/CVPR2026/papers/Qiu_ImageRAGTurbo_Towards_One-step_Text-to-Image_Generation_with_Retrieval-Augmented_Diffusion_Models_CVPR_2026_paper.pdf |
PointTPA: Dynamic Network Parameter Adaptation for 3D Scene Understanding | Siyuan Liu, Chaoqun Zheng, Xin Zhou, Tianrui Feng, Dingkang Liang, Xiang Bai | Scene-level point cloud understanding remains challenging due to diverse geometries, imbalanced category distributions, and highly varied spatial layouts. Existing methods improve object-level performance but rely on static network parameters during inference, limiting their adaptability to dynamic scene data. We propo... | 2026/pdf/Liu_PointTPA_Dynamic_Network_Parameter_Adaptation_for_3D_Scene_Understanding_CVPR_2026_paper.pdf | @InProceedings{Liu_2026_CVPR,
author = {Liu, Siyuan and Zheng, Chaoqun and Zhou, Xin and Feng, Tianrui and Liang, Dingkang and Bai, Xiang},
title = {PointTPA: Dynamic Network Parameter Adaptation for 3D Scene Understanding},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and P... | https://openaccess.thecvf.com/content/CVPR2026/papers/Liu_PointTPA_Dynamic_Network_Parameter_Adaptation_for_3D_Scene_Understanding_CVPR_2026_paper.pdf |
Dexterous World Models | Byungjun Kim, Taeksoo Kim, Junyoung Lee, Hanbyul Joo | Recent progress in 3D reconstruction has made it easy to create realistic digital twins from everyday environments. However, current digital twins remain largely static--limited to navigation and view synthesis without embodied interactivity. To bridge this gap, we introduce Dexterous World Model (DWM), an scene-action... | 2026/pdf/Kim_Dexterous_World_Models_CVPR_2026_paper.pdf | @InProceedings{Kim_2026_CVPR,
author = {Kim, Byungjun and Kim, Taeksoo and Lee, Junyoung and Joo, Hanbyul},
title = {Dexterous World Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2026},
pag... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kim_Dexterous_World_Models_CVPR_2026_paper.pdf |
Can Natural Image Autoencoders Compactly Tokenize fMRI Volumes for Long-Range Dynamics Modeling? | Peter Yongho Kim, Juhyeon Park, Jungwoo Park, Jubin Choi, Jungwoo Seo, Jiook Cha, Taesup Moon | Modeling long-range spatiotemporal dynamics in functional Magnetic Resonance Imaging (fMRI) remains a key challenge due to the high dimensionality of the four-dimensional signals. Prior voxel-based models, although demonstrating excellent performance and interpretation capabilities, are constrained by prohibitive memor... | 2026/pdf/Kim_Can_Natural_Image_Autoencoders_Compactly_Tokenize_fMRI_Volumes_for_Long-Range_CVPR_2026_paper.pdf | @InProceedings{Kim_2026_CVPR,
author = {Kim, Peter Yongho and Park, Juhyeon and Park, Jungwoo and Choi, Jubin and Seo, Jungwoo and Cha, Jiook and Moon, Taesup},
title = {Can Natural Image Autoencoders Compactly Tokenize fMRI Volumes for Long-Range Dynamics Modeling?},
booktitle = {Proceedings of the ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kim_Can_Natural_Image_Autoencoders_Compactly_Tokenize_fMRI_Volumes_for_Long-Range_CVPR_2026_paper.pdf |
You Only Erase Once: Erasing Anything without Bringing Unexpected Content | Yixing Zhu, Qing Zhang, Wenju Xu, Wei-Shi Zheng | We present YOEO, an approach for object erasure. Unlike recent diffusion-based methods which struggle to erase target objects without generating unexpected content within the masked regions due to lack of sufficient paired training data and explicit constraint on content generation, our method allows to produce high-qu... | 2026/pdf/Zhu_You_Only_Erase_Once_Erasing_Anything_without_Bringing_Unexpected_Content_CVPR_2026_paper.pdf | @InProceedings{Zhu_2026_CVPR,
author = {Zhu, Yixing and Zhang, Qing and Xu, Wenju and Zheng, Wei-Shi},
title = {You Only Erase Once: Erasing Anything without Bringing Unexpected Content},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhu_You_Only_Erase_Once_Erasing_Anything_without_Bringing_Unexpected_Content_CVPR_2026_paper.pdf |
TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens | Jiawei Ren, Michal Jan Tyszkiewicz, Jiahui Huang, Zan Gojcic | In this work, we revisit several key design choices of modern Transformer-based approaches for feed-forward 3D Gaussian Splatting (3DGS) prediction. We argue that the common practice of regressing Gaussian means as depths along camera rays is suboptimal, and instead propose to directly regress 3D mean coordinates using... | 2026/pdf/Ren_TokenGS_Decoupling_3D_Gaussian_Prediction_from_Pixels_with_Learnable_Tokens_CVPR_2026_paper.pdf | @InProceedings{Ren_2026_CVPR,
author = {Ren, Jiawei and Tyszkiewicz, Michal Jan and Huang, Jiahui and Gojcic, Zan},
title = {TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (C... | https://openaccess.thecvf.com/content/CVPR2026/papers/Ren_TokenGS_Decoupling_3D_Gaussian_Prediction_from_Pixels_with_Learnable_Tokens_CVPR_2026_paper.pdf |
NuWa: Deriving Lightweight Class-Specific Vision Transformers for Edge Devices | Ziteng Wei, Qiang He, Bing Li, Feifei Chen, Hai Jin, Yun Yang | Vision Transformers (ViTs) often need to be compressed for deployment on resource-constrained edge devices like drones and smart vehicles. However, existing model compression methods ignore that many edge devices only require the knowledge of specific classes for their applications. As a result, the derived all-class V... | 2026/pdf/Wei_NuWa_Deriving_Lightweight_Class-Specific_Vision_Transformers_for_Edge_Devices_CVPR_2026_paper.pdf | @InProceedings{Wei_2026_CVPR,
author = {Wei, Ziteng and He, Qiang and Li, Bing and Chen, Feifei and Jin, Hai and Yang, Yun},
title = {NuWa: Deriving Lightweight Class-Specific Vision Transformers for Edge Devices},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Rec... | https://openaccess.thecvf.com/content/CVPR2026/papers/Wei_NuWa_Deriving_Lightweight_Class-Specific_Vision_Transformers_for_Edge_Devices_CVPR_2026_paper.pdf |
CGHair: Compact Gaussian Hair Reconstruction with Card Clustering | Haimin Luo, Srinjay Sarkar, Albert Mosella-Montoro, Francisco Vicente Carrasco, Fernando De la Torre | We present a compact pipeline for high-fidelity hair reconstruction from multi-view images. While recent 3D Gaussian Splatting (3DGS) methods achieve realistic results, they often require millions of primitives, leading to high storage and rendering costs. Observing that hair exhibits structural and visual similarities... | 2026/pdf/Luo_CGHair_Compact_Gaussian_Hair_Reconstruction_with_Card_Clustering_CVPR_2026_paper.pdf | @InProceedings{Luo_2026_CVPR,
author = {Luo, Haimin and Sarkar, Srinjay and Mosella-Montoro, Albert and Carrasco, Francisco Vicente and De la Torre, Fernando},
title = {CGHair: Compact Gaussian Hair Reconstruction with Card Clustering},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer ... | https://openaccess.thecvf.com/content/CVPR2026/papers/Luo_CGHair_Compact_Gaussian_Hair_Reconstruction_with_Card_Clustering_CVPR_2026_paper.pdf |
SCAPO: Self-Supervised Category-Level Articulated Pose Estimation from a Single 3D Observation | Can Zhang, Gim Hee Lee | Existing methods for category-level object articulation from a single 3D observation often rely on dense supervision, multi-frame inputs, or CAD templates, and still struggle to disentangle geometry from articulation or to recover explicit joint parameters. We propose SCAPO , a self-supervised framework that estimates ... | 2026/pdf/Zhang_SCAPO_Self-Supervised_Category-Level_Articulated_Pose_Estimation_from_a_Single_3D_CVPR_2026_paper.pdf | @InProceedings{Zhang_2026_CVPR,
author = {Zhang, Can and Lee, Gim Hee},
title = {SCAPO: Self-Supervised Category-Level Articulated Pose Estimation from a Single 3D Observation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {Ju... | https://openaccess.thecvf.com/content/CVPR2026/papers/Zhang_SCAPO_Self-Supervised_Category-Level_Articulated_Pose_Estimation_from_a_Single_3D_CVPR_2026_paper.pdf |
EditMGT: Unleashing Potentials of Masked Generative Transformers in Image Editing | Wei Chow, Linfeng Li, Lingdong Kong, Zefeng Li, Qi Xu, Hang Song, Tian Ye, Xian Wang, Jinbin Bai, Shilin Xu, Xiangtai Li, Junting Pan, Shaoteng Liu, Ran Zhou, Tianshu Yang, Songhua Liu | Recent advances in diffusion models (DMs) have achieved exceptional visual quality in image editing tasks. However, the global denoising dynamics of DMs inherently conflate local editing targets with the full-image context, leading to unintended modifications in non-target regions. In this paper, we shift our attention... | 2026/pdf/Chow_EditMGT_Unleashing_Potentials_of_Masked_Generative_Transformers_in_Image_Editing_CVPR_2026_paper.pdf | @InProceedings{Chow_2026_CVPR,
author = {Chow, Wei and Li, Linfeng and Kong, Lingdong and Li, Zefeng and Xu, Qi and Song, Hang and Ye, Tian and Wang, Xian and Bai, Jinbin and Xu, Shilin and Li, Xiangtai and Pan, Junting and Liu, Shaoteng and Zhou, Ran and Yang, Tianshu and Liu, Songhua},
title = {EditMGT... | https://openaccess.thecvf.com/content/CVPR2026/papers/Chow_EditMGT_Unleashing_Potentials_of_Masked_Generative_Transformers_in_Image_Editing_CVPR_2026_paper.pdf |
World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models | Eunsu Kim, Junyeong Park, Na Min An, Junseong Kim, Hitesh Laxmichand Patel, Jiho Jin, Julia Kruk, Amit Agarwal, Srikant Panda, Fenal Ashokbhai Ilasariya, Hyunjung Shim, Alice Oh | In a globalized world, cultural elements from diverse origins frequently appear together within a single visual scene. We refer to these as culture mixing scenarios, yet how Large Vision-Language Models (LVLMs) perceive them remains underexplored. We investigate culture mixing as a critical challenge for LVLMs and exam... | 2026/pdf/Kim_World_in_a_Frame_Understanding_Culture_Mixing_as_a_New_CVPR_2026_paper.pdf | @InProceedings{Kim_2026_CVPR,
author = {Kim, Eunsu and Park, Junyeong and An, Na Min and Kim, Junseong and Patel, Hitesh Laxmichand and Jin, Jiho and Kruk, Julia and Agarwal, Amit and Panda, Srikant and Ilasariya, Fenal Ashokbhai and Shim, Hyunjung and Oh, Alice},
title = {World in a Frame: Understanding... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kim_World_in_a_Frame_Understanding_Culture_Mixing_as_a_New_CVPR_2026_paper.pdf |
E3AD: An Emotion-Aware Vision-Language-Action Model for Human-Centric End-to-End Autonomous Driving | Yihong Tang, Haicheng Liao, Tong Nie, Junlin He, Ao Qu, Kehua Chen, Wei Ma, Zhenning Li, Lijun Sun, Chengzhong Xu | End-to-end autonomous driving (AD) systems increasingly adopt vision-language-action (VLA) models, yet they ignore the passenger's emotional state, which is central to comfort and AD acceptance. We introduce Open-Domain End-to-End (OD-E2E) AD, where an autonomous vehicle must interpret free-form natural-language comman... | 2026/pdf/Tang_E3AD_An_Emotion-Aware_Vision-Language-Action_Model_for_Human-Centric_End-to-End_Autonomous_Driving_CVPR_2026_paper.pdf | @InProceedings{Tang_2026_CVPR,
author = {Tang, Yihong and Liao, Haicheng and Nie, Tong and He, Junlin and Qu, Ao and Chen, Kehua and Ma, Wei and Li, Zhenning and Sun, Lijun and Xu, Chengzhong},
title = {E3AD: An Emotion-Aware Vision-Language-Action Model for Human-Centric End-to-End Autonomous Driving},
... | https://openaccess.thecvf.com/content/CVPR2026/papers/Tang_E3AD_An_Emotion-Aware_Vision-Language-Action_Model_for_Human-Centric_End-to-End_Autonomous_Driving_CVPR_2026_paper.pdf |
Frequency-domain Manipulation for Face Obfuscation | Jintae Kim, Keunsoo Ko, Chang-Su Kim | Facial image datasets have become essential resources for various face analysis tasks, but their use raises significant privacy concerns. To address this issue, face obfuscation has emerged as a practical approach to hide identity from humans while retaining cues decipherable by machines. However, existing methods ofte... | 2026/pdf/Kim_Frequency-domain_Manipulation_for_Face_Obfuscation_CVPR_2026_paper.pdf | @InProceedings{Kim_2026_CVPR,
author = {Kim, Jintae and Ko, Keunsoo and Kim, Chang-Su},
title = {Frequency-domain Manipulation for Face Obfuscation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2026},... | https://openaccess.thecvf.com/content/CVPR2026/papers/Kim_Frequency-domain_Manipulation_for_Face_Obfuscation_CVPR_2026_paper.pdf |
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