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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000"
19489 条 记 录,以下是4801-4810 订阅
排序:
Context-aware Biaffine Localizing Network for Temporal Sentence Grounding
Context-aware Biaffine Localizing Network for Temporal Sente...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Liu, Daizong Qu, Xiaoye Dong, Jianfeng Zhou, Pan Cheng, Yu Wei, Wei Xu, Zichuan Xie, Yulai Huazhong Univ Sci & Technol Wuhan Hubei Peoples R China Huawei Cloud Shenzhen Peoples R China Zhejiang Gongshang Univ Hangzhou Zhejiang Peoples R China Microsoft AI Redmond WA USA Dalian Univ Technol Dalian Liaoning Peoples R China
This paper addresses the problem of temporal sentence grounding (TSG), which aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence query. Previous works either compare pre-... 详细信息
来源: 评论
recognition of Symmetry Structure by Use of Gestalt Algebra
Recognition of Symmetry Structure by Use of Gestalt Algebra
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26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Michaelsen, Eckart Muench, David Arens, Michael Fraunhofer IOSB D-76275 Ettlingen Germany
While most approaches to symmetry detection in machine vision try to explain the gray-values or colors of the pixels, Gestalt algebra has no room for such measurement data. The entities (i.e. Gestalten) are only defin... 详细信息
来源: 评论
Pixel-Guided Dual-Branch Attention Network for Joint Image Deblurring and Super-Resolution
Pixel-Guided Dual-Branch Attention Network for Joint Image D...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Xi, Si Wei, Jia Zhang, Weidong Netease Games AI Lab Hangzhou Peoples R China
Image deblurring and super-resolution (SR) are computer vision tasks aiming to restore image detail and spatial scale, respectively. Besides, only a few recent works of literature contribute to this task, as conventio... 详细信息
来源: 评论
Rethinking computer-aided Tuberculosis Diagnosis
Rethinking Computer-aided Tuberculosis Diagnosis
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Liu, Yun Wu, Yu-Huan Ban, Yunfeng Wang, Huifang Cheng, Ming-Ming Nankai Univ Coll Comp Sci TKLNDST Tianjin Peoples R China InferVision Beijing Peoples R China
As a serious infectious disease, tuberculosis (TB) is one of the major threats to human health worldwide, leading to millions of deaths every year. Although early diagnosis and treatment can greatly improve the chance... 详细信息
来源: 评论
Improving Adversarially Robust Few-shot Image Classification with Generalizable Representations
Improving Adversarially Robust Few-shot Image Classification...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Dong, Junhao Wang, Yuan Lai, Jianhuang Xie, Xiaohua Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou Peoples R China Guangdong Prov Key Lab Informat Secur Technol Guangzhou Peoples R China Minist Educ Key Lab Machine Intelligence & Adv Comp Beijing Peoples R China
Few-Shot Image Classification (FSIC) aims to recognize novel image classes with limited data, which is significant in practice. In this paper, we consider the FSIC problem in the case of adversarial examples. This is ... 详细信息
来源: 评论
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing  31
Weakly-Supervised Semantic Segmentation Network with Deep Se...
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31st ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Huang, Zilong Wang, Xinggang Wang, Jiasi Liu, Wenyu Wang, Jingdong Huazhong Univ Sci & Technol Sch Elect Informat & Commun Wuhan Hubei Peoples R China Microsoft Res Asia Beijing Peoples R China
This paper studies the problem of learning image semantic segmentation networks only using image-level labels as supervision, which is important since it can significantly reduce human annotation efforts. Recent state... 详细信息
来源: 评论
ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior
ISNAS-DIP: Image-Specific Neural Architecture Search for Dee...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Arican, Metin Ersin Kara, Ozgur Bredell, Gustav Konukoglu, Ender Bogazici Univ Dept Elect & Elect Engn Istanbul Turkey Swiss Fed Inst Technol Dept Informat Technol & Elect Engn Zurich Switzerland
Recent works show that convolutional neural network (CNN) architectures have a spectral bias towards lower frequencies, which has been leveraged for various image restoration tasks in the Deep Image Prior (DIP) framew... 详细信息
来源: 评论
A Proposal-based Paradigm for Self-supervised Sound Source Localization in Videos
A Proposal-based Paradigm for Self-supervised Sound Source L...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Xuan, Hanyu Wu, Zhiliang Yang, Jian Yan, Yan Alameda-Pineda, Xavier Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing Peoples R China IIT Dept Comp Sci Chicago IL 60616 USA Univ Grenoble Alpes LJK Grenoble INP INRIACNRS F-38000 Grenoble France
Humans can easily recognize where and how the sound is produced via watching a scene and listening to corresponding audio cues. To achieve such cross-modal perception on machines, existing methods only use the maps ge... 详细信息
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Progressive Relation Learning for Group Activity recognition
Progressive Relation Learning for Group Activity Recognition
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Hu, Guyue Cui, Bo He, Yuan Yu, Shan Chinese Acad Sci CASIA Natl Lab Pattern Recognit Brainnetome Ctr Inst Automat Beijing Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China
Group activities usually involve spatiotemporal dynamics among many interactive individuals, while only a few participants at several key frames essentially define the activity. Therefore, effectively modeling the gro... 详细信息
来源: 评论
Semantic Graph Convolutional Networks for 3D Human Pose Regression  32
Semantic Graph Convolutional Networks for 3D Human Pose Regr...
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32nd ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhao, Long Peng, Xi Tian, Yu Kapadia, Mubbasir Metaxas, Dimitris N. Rutgers State Univ New Brunswick NJ 22894 USA SUNY Binghamton Binghamton NY 13902 USA
In this paper, we study the problem of learning Graph Convolutional Networks (GCNs) for regression. Current architectures of GCNs are limited to the small receptive field of convolution filters and shared transformati... 详细信息
来源: 评论