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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops"
23198 条 记 录,以下是4941-4950 订阅
排序:
NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections
NeRF in the Wild: Neural Radiance Fields for Unconstrained P...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Martin-Brualla, Ricardo Radwan, Noha Sajjadi, Mehdi S. M. Barron, Jonathan T. Dosovitskiy, Alexey Duckworth, Daniel Google Res Mountain View CA 94043 USA
We present a learning-based method for synthesizing novel views of complex scenes using only unstructured collections of in-the-wild photographs. We build on Neural Radiance Fields (NeRF), which uses the weights of a ... 详细信息
来源: 评论
Mask Guided Matting via Progressive Refinement Network
Mask Guided Matting via Progressive Refinement Network
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yu, Qihang Zhang, Jianming Zhang, He Wang, Yilin Lin, Zhe Xu, Ning Bai, Yutong Yuille, Alan Johns Hopkins Univ Baltimore MD 21218 USA Adobe San Jose CA USA
We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance. MG Matting leverages a network (PRN) design which encourages the matting model to provide self-guidance to ... 详细信息
来源: 评论
Visual Semantic Role Labeling for Video Understanding
Visual Semantic Role Labeling for Video Understanding
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Sadhu, Arka Gupta, Tanmay Yatskar, Mark Nevatia, Ram Kembhavi, Aniruddha Univ Southern Calif Los Angeles CA 90007 USA Univ Penn Philadelphia PA 19104 USA PRIOR Allen Inst AI Seattle WA USA PRIOR AI2 Seattle WA USA
We propose a new framework for understanding and representing related salient events in a video using visual semantic role labeling. We represent videos as a set of related events, wherein each event consists of a ver... 详细信息
来源: 评论
Disentangling Label Distribution for Long-tailed Visual recognition
Disentangling Label Distribution for Long-tailed Visual Reco...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hong, Youngkyu Han, Seungju Choi, Kwanghee Seo, Seokjun Kim, Beomsu Chang, Buru Hyperconnect Seoul South Korea
The current evaluation protocol of long-tailed visual recognition trains the classification model on the long-tailed source label distribution and evaluates its performance on the uniform target label distribution. Su... 详细信息
来源: 评论
Counterfactual VQA: A Cause-Effect Look at Language Bias
Counterfactual VQA: A Cause-Effect Look at Language Bias
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Niu, Yulei Tang, Kaihua Zhang, Hanwang Lu, Zhiwu Hua, Xian-Sheng Wen, Ji-Rong Nanyang Technol Univ Singapore Singapore Renmin Univ China Gaoling Sch Artificial Intelligence Beijing Peoples R China Beijing Key Lab Big Data Management & Anal Method Beijing Peoples R China Alibaba Grp Damo Acad Hangzhou Peoples R China
VQA models may tend to rely on language bias as a shortcut and thus fail to sufficiently learn the multi-modal knowledge from both vision and language. Recent debiasing methods proposed to exclude the language prior d... 详细信息
来源: 评论
Self-supervised Motion Learning from Static Images
Self-supervised Motion Learning from Static Images
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Huang, Ziyuan Zhang, Shiwei Jiang, Jianwen Tang, Mingqian Jin, Rong Ang, Marcelo H., Jr. Natl Univ Singapore Singapore Singapore Alibaba Grp Hangzhou Peoples R China
Motions are reflected in videos as the movement of pixels, and actions are essentially patterns of inconsistent motions between the foreground and the background. To well distinguish the actions, especially those with... 详细信息
来源: 评论
Weakly-Supervised Physically Unconstrained Gaze Estimation
Weakly-Supervised Physically Unconstrained Gaze Estimation
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Kothari, Rakshit De Mello, Shalini Iqbal, Umar Byeon, Wonmin Park, Seonwook Kautz, Jan NVIDIA Santa Clara CA 95051 USA Rochester Inst Technol Rochester NY 14623 USA Lunit Inc Seoul South Korea
A major challenge for physically unconstrained gaze estimation is acquiring training data with 3D gaze annotations for in-the-wild and outdoor scenarios. In contrast, videos of human interactions in unconstrained envi... 详细信息
来源: 评论
Self-supervised Video Representation Learning by Context and Motion Decoupling
Self-supervised Video Representation Learning by Context and...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Huang, Lianghua Liu, Yu Wang, Bin Pan, Pan Xu, Yinghui Jin, Rong Alibaba Grp Machine Intelligence Technol Lab Hangzhou Peoples R China
A key challenge in self-supervised video representation learning is how to effectively capture motion information besides context bias. While most existing works implicitly achieve this with video-specific pretext tas... 详细信息
来源: 评论
Representing Videos as Discriminative Sub-graphs for Action recognition
Representing Videos as Discriminative Sub-graphs for Action ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Dong Qiu, Zhaofan Pan, Yingwei Yao, Ting Li, Houqiang Mei, Tao Univ Sci & Technol China Hefei Peoples R China JD AI Res Beijing Peoples R China
Human actions are typically of combinatorial structures or patterns, i.e., subjects, objects, plus spatio-temporal interactions in between. Discovering such structures is therefore a rewarding way to reason about the ... 详细信息
来源: 评论
Spherical Confidence Learning for Face recognition
Spherical Confidence Learning for Face Recognition
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Shen Xu, Jianqing Xu, Xiaqing Shen, Pengcheng Li, Shaoxin Hooi, Bryan Natl Univ Singapore Inst Data Sci Singapore Singapore Tencent Youtu Lab Shenzhen Peoples R China Aibee Beijing Peoples R China
An emerging line of research has found that spherical spaces better match the underlying geometry of facial images, as evidenced by the state-of-the-art facial recognition methods which benefit empirically from spheri... 详细信息
来源: 评论