paper_id uint32 0 4.07k | title stringlengths 8 154 | authors listlengths 1 40 | cvf_url stringlengths 86 196 | pdf_url stringlengths 87 197 | supp_url stringlengths 98 147 ⌀ | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
values | bibtex large_stringlengths 308 1.06k | abstract large_stringlengths 562 2.77k | embedding listlengths 768 768 |
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0 | Generalizable Structure-Aware Keypoint Correspondence for Category-Unified 3D Single Object Tracking | [
"Jie Xiao",
"Yinchao Ma",
"Yuyang Tang",
"Dengqing Yang",
"Jianpeng Yang",
"Xu Zhou",
"Qiao Li",
"Wenfei Yang",
"Tianzhu Zhang"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Xiao_Generalizable_Structure-Aware_Keypoint_Correspondence_for_Category-Unified_3D_Single_Object_Tracking_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Xiao_Generalizable_Structure-Aware_Keypoint_Correspondence_for_Category-Unified_3D_Single_Object_Tracking_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Xiao_Generalizable_Structure-Aware_Keypoint_CVPR_2026_supplemental.pdf | null | null | @InProceedings{Xiao_2026_CVPR,
author = {Xiao, Jie and Ma, Yinchao and Tang, Yuyang and Yang, Dengqing and Yang, Jianpeng and Zhou, Xu and Li, Qiao and Yang, Wenfei and Zhang, Tianzhu},
title = {Generalizable Structure-Aware Keypoint Correspondence for Category-Unified 3D Single Object Tracking},
boo... | 3D single object tracking (SOT) in point clouds is essential for real-world 3D perception, yet it remains challenging due to data sparsity and large variations in scale and structure across diverse object categories. Most existing methods rely on a category-specific paradigm that trains separate models for each class, ... | [
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1 | DirectFisheye-GS: Enabling Native Fisheye Input in Gaussian Splatting with Cross-View Joint Optimization | [
"Zhengxian Yang",
"Fei Xie",
"Xutao Xue",
"Rui Zhang",
"Taicheng Huang",
"Yang Liu",
"Mengqi Ji",
"Tao Yu"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Yang_DirectFisheye-GS_Enabling_Native_Fisheye_Input_in_Gaussian_Splatting_with_Cross-View_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Yang_DirectFisheye-GS_Enabling_Native_Fisheye_Input_in_Gaussian_Splatting_with_Cross-View_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Yang_DirectFisheye-GS_Enabling_Native_CVPR_2026_supplemental.zip | 2604.00648 | cvf | @InProceedings{Yang_2026_CVPR,
author = {Yang, Zhengxian and Xie, Fei and Xue, Xutao and Zhang, Rui and Huang, Taicheng and Liu, Yang and Ji, Mengqi and Yu, Tao},
title = {DirectFisheye-GS: Enabling Native Fisheye Input in Gaussian Splatting with Cross-View Joint Optimization},
booktitle = {Proceedin... | 3D Gaussian Splatting (3DGS) has enabled efficient 3D scene reconstruction from everyday images with real-time, high-fidelity rendering, greatly advancing VR/AR applications. Fisheye cameras, with their wider field of view (FOV), promise high-quality reconstructions from fewer inputs and have recently attracted much at... | [
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2 | CompBench: Benchmarking Complex Instruction-guided Image Editing | [
"Bohan Jia",
"Wenxuan Huang",
"Yuntian Tang",
"Junbo Qiao",
"Jincheng Liao",
"Shaosheng Cao",
"Fei Zhao",
"Zhaopeng Feng",
"Zhouhong Gu",
"Zhenfei Yin",
"Lei Bai",
"Wanli Ouyang",
"Lin Chen",
"Fei Zhao",
"Zihan Wang",
"Yuan Xie",
"Shaohui Lin"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Jia_CompBench_Benchmarking_Complex_Instruction-guided_Image_Editing_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Jia_CompBench_Benchmarking_Complex_Instruction-guided_Image_Editing_CVPR_2026_paper.pdf | null | 2505.12200 | cvf | @InProceedings{Jia_2026_CVPR,
author = {Jia, Bohan and Huang, Wenxuan and Tang, Yuntian and Qiao, Junbo and Liao, Jincheng and Cao, Shaosheng and Zhao, Fei and Feng, Zhaopeng and Gu, Zhouhong and Yin, Zhenfei and Bai, Lei and Ouyang, Wanli and Chen, Lin and Zhao, Fei and Wang, Zihan and Xie, Yuan and Lin, Shaohu... | While real-world applications increasingly demand intricate scene manipulation, existing instruction-guided image editing benchmarks often oversimplify task complexity and lack comprehensive, fine-grained instructions. To bridge this gap, we introduce CompBench, a large-scale benchmark specifically designed for complex... | [
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3 | Choreographing a World of Dynamic Objects | [
"Yanzhe Lyu",
"Chen Geng",
"Karthik Dharmarajan",
"Yunzhi Zhang",
"Hadi Alzayer",
"Shangzhe Wu",
"Jiajun Wu"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Lyu_Choreographing_a_World_of_Dynamic_Objects_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Lyu_Choreographing_a_World_of_Dynamic_Objects_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Lyu_Choreographing_a_World_CVPR_2026_supplemental.pdf | 2601.04194 | cvf | @InProceedings{Lyu_2026_CVPR,
author = {Lyu, Yanzhe and Geng, Chen and Dharmarajan, Karthik and Zhang, Yunzhi and Alzayer, Hadi and Wu, Shangzhe and Wu, Jiajun},
title = {Choreographing a World of Dynamic Objects},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Rec... | Dynamic objects in our physical 4D (3D + time) world are constantly evolving, deforming, and interacting with other objects, leading to diverse 4D scene dynamics. In this paper, we present a universal generative pipeline, CHORD, for CHOReographing Dynamic objects and scenes and synthesizing this type of phenomena. Trad... | [
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4 | Spk2VidNet: A Hierarchical Recurrent Architecture for High-Fidelity Video Reconstruction from Long Spike-Camera Streams | [
"Yuanlin Wang",
"Ruiqin Xiong",
"Jiyu Xie",
"Zhenkun Zhu",
"Zhaofei Yu",
"Xiaopeng Fan",
"Tiejun Huang"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Wang_Spk2VidNet_A_Hierarchical_Recurrent_Architecture_for_High-Fidelity_Video_Reconstruction_from_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Wang_Spk2VidNet_A_Hierarchical_Recurrent_Architecture_for_High-Fidelity_Video_Reconstruction_from_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Wang_Spk2VidNet_A_Hierarchical_CVPR_2026_supplemental.zip | null | null | @InProceedings{Wang_2026_CVPR,
author = {Wang, Yuanlin and Xiong, Ruiqin and Xie, Jiyu and Zhu, Zhenkun and Yu, Zhaofei and Fan, Xiaopeng and Huang, Tiejun},
title = {Spk2VidNet: A Hierarchical Recurrent Architecture for High-Fidelity Video Reconstruction from Long Spike-Camera Streams},
booktitle = ... | Spike camera is a neuromorphic vision sensor with ultra-high temporal resolution, capable of capturing fast-moving scenes by firing a stream of binary spikes. However, its relatively low spatial resolution limits the acquisition of fine-grained visual details, motivating research on spike camera super resolution (SCSR)... | [
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5 | Continual Distillation of Teachers from Different Domains | [
"Nicolas Michel",
"Maorong Wang",
"Jiangpeng He",
"Toshihiko Yamasaki"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Michel_Continual_Distillation_of_Teachers_from_Different_Domains_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Michel_Continual_Distillation_of_Teachers_from_Different_Domains_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Michel_Continual_Distillation_of_CVPR_2026_supplemental.pdf | 2605.04059 | cvf | @InProceedings{Michel_2026_CVPR,
author = {Michel, Nicolas and Wang, Maorong and He, Jiangpeng and Yamasaki, Toshihiko},
title = {Continual Distillation of Teachers from Different Domains},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
mon... | Deep learning models continue to scale, with some requiring more storage than many large-scale datasets. Thus, we introduce a new paradigm: Continual Distillation (CD), where a student learns sequentially from a stream of teacher models without retaining access to earlier teachers. CD faces two challenges: teacher trai... | [
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6 | GT-SVJ: Generative-Transformer-Based Self-Supervised Video Judge For Efficient Video Reward Modeling | [
"Shivanshu Shekhar",
"Uttaran Bhattacharya",
"Raghavendra Addanki",
"Mehrab Tanjim",
"Somdeb Sarkhel",
"Tong Zhang"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Shekhar_GT-SVJ_Generative-Transformer-Based_Self-Supervised_Video_Judge_For_Efficient_Video_Reward_Modeling_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Shekhar_GT-SVJ_Generative-Transformer-Based_Self-Supervised_Video_Judge_For_Efficient_Video_Reward_Modeling_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Shekhar_GT-SVJ_Generative-Transformer-Based_Self-Supervised_CVPR_2026_supplemental.zip | 2602.05202 | cvf | @InProceedings{Shekhar_2026_CVPR,
author = {Shekhar, Shivanshu and Bhattacharya, Uttaran and Addanki, Raghavendra and Tanjim, Mehrab and Sarkhel, Somdeb and Zhang, Tong},
title = {GT-SVJ: Generative-Transformer-Based Self-Supervised Video Judge For Efficient Video Reward Modeling},
booktitle = {Proce... | Aligning video generative models with human preferences remains challenging: current approaches rely on Vision-Language Models (VLMs) for reward modeling, but these models struggle to capture subtle temporal dynamics. We propose a fundamentally different approach: repurposing video generative models, which are inherent... | [
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7 | Beyond Euclidean Gossip: KL-Barycentric Consensus on Heterogeneous and Imbalanced Images | [
"Lu Xu",
"Guosheng Yin"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Xu_Beyond_Euclidean_Gossip_KL-Barycentric_Consensus_on_Heterogeneous_and_Imbalanced_Images_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Xu_Beyond_Euclidean_Gossip_KL-Barycentric_Consensus_on_Heterogeneous_and_Imbalanced_Images_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Xu_Beyond_Euclidean_Gossip_CVPR_2026_supplemental.pdf | null | null | @InProceedings{Xu_2026_CVPR,
author = {Xu, Lu and Yin, Guosheng},
title = {Beyond Euclidean Gossip: KL-Barycentric Consensus on Heterogeneous and Imbalanced Images},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
yea... | Fully decentralized deep learning removes global servers and ensures local data privacy. However, Euclidean consensus, averaging weights, gradients or momentum, may degrade under the situations with non-i.i.d. (non-independent and identically distributed) data and client size imbalance. We propose a geometry-aware appr... | [
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8 | HybridDriveVLA: Vision-Language-Action Model with Visual CoT reasoning and ToT Evaluation for Autonomous Driving | [
"Yipene Cedric Francois Bassole",
"Sungwoo Kim",
"Jiwoo Jung",
"Yunsick Sung"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Bassole_HybridDriveVLA_Vision-Language-Action_Model_with_Visual_CoT_reasoning_and_ToT_Evaluation_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Bassole_HybridDriveVLA_Vision-Language-Action_Model_with_Visual_CoT_reasoning_and_ToT_Evaluation_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Bassole_HybridDriveVLA_Vision-Language-Action_Model_CVPR_2026_supplemental.zip | null | null | @InProceedings{Bassole_2026_CVPR,
author = {Bassole, Yipene Cedric Francois and Kim, Sungwoo and Jung, Jiwoo and Sung, Yunsick},
title = {HybridDriveVLA: Vision-Language-Action Model with Visual CoT reasoning and ToT Evaluation for Autonomous Driving},
booktitle = {Proceedings of the IEEE/CVF Confere... | Vision-Language-Action (VLA) models are emerging as an important technology in autonomous driving, recognized for their sophisticated reasoning and interpretability. However, traditional VLA models often rely on image-to-text with Chain-of-Thought (CoT) reasoning, which converts sequential visual scenes into textual sy... | [
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9 | Training-free, Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models | [
"Wongi Jeong",
"Hoigi Seo",
"Se Young Chun"
] | https://openaccess.thecvf.com/content/CVPR2026/html/Jeong_Training-free_Perceptually_Consistent_Low-Resolution_Previews_with_High-Resolution_Image_for_Efficient_CVPR_2026_paper.html | https://openaccess.thecvf.com/content/CVPR2026/papers/Jeong_Training-free_Perceptually_Consistent_Low-Resolution_Previews_with_High-Resolution_Image_for_Efficient_CVPR_2026_paper.pdf | https://openaccess.thecvf.com/content/CVPR2026/supplemental/Jeong_Training-free_Perceptually_Consistent_CVPR_2026_supplemental.pdf | 2604.09227 | cvf | @InProceedings{Jeong_2026_CVPR,
author = {Jeong, Wongi and Seo, Hoigi and Chun, Se Young},
title = {Training-free, Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer V... | Image generative models have become indispensable tools to yield exquisite high-resolution (HR) images for everyone, ranging from general users to professional designers. However, a desired outcome often requires generating a large number of HR images with different prompts and seeds, resulting in high computational co... | [
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