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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops"
12859 条 记 录,以下是4801-4810 订阅
排序:
Scale-aware Automatic Augmentation for Object Detection
Scale-aware Automatic Augmentation for Object Detection
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Chen, Yukang Li, Yanwei Kong, Tao Qi, Lu Chu, Ruihang Li, Lei Jia, Jiaya Chinese Univ Hong Kong Hong Kong Peoples R China ByteDance AI Lab Beijing Peoples R China SmartMore Hong Kong Peoples R China
We propose Scale-aware AutoAug to learn data augmentation policies for object detection. We define a new scaleaware search space, where both image- and box-level augmentations are designed for maintaining scale invari... 详细信息
来源: 评论
One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation
One Thing One Click: A Self-Training Approach for Weakly Sup...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Liu, Zhengzhe Qi, Xiaojuan Fu, Chi-Wing Chinese Univ Hong Kong Hong Kong Peoples R China Univ Hong Kong Hong Kong Peoples R China
Point cloud semantic segmentation often requires large-scale annotated training data, but clearly, point-wise labels are too tedious to prepare. While some recent methods propose to train a 3D network with small perce... 详细信息
来源: 评论
Detecting Human-Object Interaction via Fabricated Compositional Learning
Detecting Human-Object Interaction via Fabricated Compositio...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Hou, Zhi Yu, Baosheng Qiao, Yu Peng, Xiaojiang Tao, Dacheng Univ Sydney Fac Engn Sch Comp Sci Sydney NSW Australia Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Shanghai AI Lab Shanghai Peoples R China Shenzhen Technol Univ Shenzhen Peoples R China
Human-Object Interaction (HOI) detection, inferring the relationships between human and objects from images/videos, is a fundamental task for high-level scene understanding. However, HOI detection usually suffers from... 详细信息
来源: 评论
Affordance Transfer Learning for Human-Object Interaction Detection
Affordance Transfer Learning for Human-Object Interaction De...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Hou, Zhi Yu, Baosheng Qiao, Yu Peng, Xiaojiang Tao, Dacheng Univ Sydney Fac Engn Sch Comp Sci Sydney NSW Australia Chinese Acad Sci Shenzhen Inst Adv Technol Beijing Peoples R China Shanghai AI Lab Shanghai Peoples R China Shenzhen Technol Univ Shenzhen Peoples R China
Reasoning the human-object interactions (HOI) is essential for deeper scene understanding, while object affordances (or functionalities) are of great importance for human to discover unseen HOIs with novel objects. In... 详细信息
来源: 评论
Learning Spatially-Variant MAP Models for Non-blind Image Deblurring
Learning Spatially-Variant MAP Models for Non-blind Image De...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Dong, Jiangxin Roth, Stefan Schiele, Bernt Saarland Informat Campus MPI Informat Saarbrucken Germany Tech Univ Darmstadt Darmstadt Germany Hessian AI Darmstadt Germany
The classical maximum a-posteriori (MAP) framework for non-blind image deblurring requires defining suitable data and regularization terms, whose interplay yields the desired clear image through optimization. The vast... 详细信息
来源: 评论
CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning
CoLA: Weakly-Supervised Temporal Action Localization with Sn...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Can Cao, Meng Yang, Dongming Chen, Jie Zou, Yuexian Peking Univ Sch Elect & Comp Engn Beijing Peoples R China Peng Cheng Lab Shenzhen Peoples R China
Weakly-supervised temporal action localization (WS-TAL) aims to localize actions in untrimmed videos with only video-level labels. Most existing models follow the "localization by classification" procedure: ... 详细信息
来源: 评论
Meta-Mining Discriminative Samples for Kinship Verification
Meta-Mining Discriminative Samples for Kinship Verification
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Li, Wanhua Wang, Shiwei Lu, Jiwen Feng, Jianjiang Zhou, Jie Tsinghua Univ Dept Automat Beijing Peoples R China Beijing Natl Res Ctr Informat Sci & Technol Beijing Peoples R China Beijing Univ Posts & Telecommun Sch Modern Post Beijing Peoples R China
Kinship verification aims to find out whether there is a kin relation for a given pair of facial images. Kinship verification databases are born with unbalanced data. For a database with N positive kinship pairs, we n... 详细信息
来源: 评论
Semantic Image Matting
Semantic Image Matting
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Sun, Yanan Tang, Chi-Keung Tai, Yu-Wing HKUST Hong Kong Peoples R China Kuaishou Technol Beijing Peoples R China
Natural image matting separates the foreground from background in fractional occupancy which can be caused by highly transparent objects, complex foreground (e.g., net or tree), and/or objects containing very fine det... 详细信息
来源: 评论
Evaluating and Improving Compositional Text-to-Visual Generation
Evaluating and Improving Compositional Text-to-Visual Genera...
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ieee computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Baiqi Li Zhiqiu Lin Deepak Pathak Jiayao Li Yixin Fei Kewen Wu Xide Xia Pengchuan Zhang Graham Neubig Deva Ramanan CMU Meta
While text-to-visual models now produce photo-realistic images and videos, they struggle with compositional text prompts involving attributes, relationships, and higher-order reasoning such as logic and comparison. In... 详细信息
来源: 评论
SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification
SimPLE: Similar Pseudo Label Exploitation for Semi-Supervise...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Hu, Zijian Yang, Zhengyu Hu, Xuefeng Nevatia, Ram Univ Southern Calif Los Angeles CA 90007 USA
A common classification task situation is where one has a large amount of data available for training, but only a small portion is annotated with class labels. The goal of semi-supervised training, in this context, is... 详细信息
来源: 评论