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检索条件"任意字段=2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011"
21099 条 记 录,以下是4991-5000 订阅
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Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification
Learning to Generalize Unseen Domains via Memory-based Multi...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhao, Yuyang Zhong, Zhun Yang, Fengxiang Luo, Zhiming Lin, Yaojin Li, Shaozi Sebe, Nicu Xiamen Univ Sch Informat Dept Artificial Intelligence Xiamen Fujian Peoples R China Univ Trento Dept Informat Engn & Comp Sci Trento Italy Xiamen Univ Inst Artificial Intelligence Xiamen Fujian Peoples R China Minnan Normal Univ Zhangzhou Fujian Peoples R China Xiamen Univ Xiamen Fujian Peoples R China
Recent advances in person re-identification (ReID) obtain impressive accuracy in the supervised and unsupervised learning settings. However, most of the existing methods need to train a new model for a new domain by a... 详细信息
来源: 评论
S3 : Learnable Sparse Signal Superdensity for Guided Depth Estimation
<i>S</i><SUP>3</SUP> : Learnable Sparse Signal Superdensity ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Huang, Yu-Kai Liu, Yueh-Cheng Wu, Tsung-Han Su, Hung-Ting Chang, Yu-Cheng Tsou, Tsung-Lin Wang, Yu-An Hsu, Winston H. Natl Taiwan Univ Taipei Taiwan
Dense depth estimation plays a key role in multiple applications such as robotics, 3D reconstruction, and augmented reality. While sparse signal, e.g., LiDAR and Radar, has been leveraged as guidance for enhancing den... 详细信息
来源: 评论
Open-book Video Captioning with Retrieve-Copy-Generate Network
Open-book Video Captioning with Retrieve-Copy-Generate Netwo...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhang, Ziqi Qi, Zhongang Yuan, Chunfeng Shan, Ying Li, Bing Deng, Ying Hu, Weiming Chinese Acad Sci Inst Automat NLPR Beijing Peoples R China Tencent PCG Appl Res Ctr ARC Shenzhen Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing Peoples R China Nanchang Hangkong Univ Sch Aeronaut Mfg Engn Nanchang Jiangxi Peoples R China
In this paper, we convert traditional video captioning task into a new paradigm, i.e., Open-book Video Captioning, which generates natural language under the prompts of video-content-relevant sentences, not limited to... 详细信息
来源: 评论
Multimodal Prompting with Missing Modalities for Visual recognition
Multimodal Prompting with Missing Modalities for Visual Reco...
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conference on computer vision and pattern recognition (cvpr)
作者: Yi-Lun Lee Yi-Hsuan Tsai Wei-Chen Chiu Chen-Yu Lee National Yang Ming Chiao Tung University Google
In this paper, we tackle two challenges in multimodal learning for visual recognition: 1) when missing-modality occurs either during training or testing in real-world situations; and 2) when the computation resources ...
来源: 评论
Spk2ImgNet: Learning to Reconstruct Dynamic Scene from Continuous Spike Stream
Spk2ImgNet: Learning to Reconstruct Dynamic Scene from Conti...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhao, Jing Xiong, Ruiqin Liu, Hangfan Zhang, Jian Huang, Tiejun Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China Univ Penn Ctr Biomed Image Comp & Analyt Philadelphia PA 19104 USA Peking Univ Shenzhen Grad Sch Beijing Peoples R China
The recently invented retina-inspired spike camera has shown great potential for capturing dynamic scenes. Different from the conventional digital cameras that compact the photoelectric information within the exposure... 详细信息
来源: 评论
GenHowTo: Learning to Generate Actions and State Transformations from Instructional Videos
GenHowTo: Learning to Generate Actions and State Transformat...
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conference on computer vision and pattern recognition (cvpr)
作者: Tomáš Souček Dima Damen Michael Wray Ivan Laptev Josef Sivic CIIRC CTU Czech Institute of Informatics Robotics and Cybernetics at the Czech Technical University in Prague. University of Bristol MBZUAI Mohamed bin Zayed University of Artificial Intelligence.
We address the task of generating temporally consistent and physically plausible images of actions and object state transformations. Given an input image and a text prompt describing the targeted transformation, our g... 详细信息
来源: 评论
Brain Decodes Deep Nets
Brain Decodes Deep Nets
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conference on computer vision and pattern recognition (cvpr)
作者: Huzheng Yang James Gee Jianbo Shi University of Pennsylvania
We developed a tool for visualizing and analyzing large pre-trained vision models by mapping them onto the brain, thus exposing their hidden inside. Our innovation arises from a surprising usage of brain encoding: pre... 详细信息
来源: 评论
Learned Scanpaths Aid Blind Panoramic Video Quality Assessment
Learned Scanpaths Aid Blind Panoramic Video Quality Assessme...
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conference on computer vision and pattern recognition (cvpr)
作者: Kanglong Fan Wen Wen Mu Li Yifan Peng Kede Ma City University of Hong Kong Harbin Institute of Technology Shenzhen The University of Hong Kong
Panoramic videos have the advantage of providing an immersive and interactive viewing experience. Nevertheless, their spherical nature gives rise to various and uncertain user viewing behaviors, which poses significan... 详细信息
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Context-Based and Diversity-Driven Specificity in Compositional Zero-Shot Learning
Context-Based and Diversity-Driven Specificity in Compositio...
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conference on computer vision and pattern recognition (cvpr)
作者: Yun Li Zhe Liu Hang Chen Lina Yao CSIRO‘s Data61 Bytedance Ltd. Snap Inc.
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object pairs based on a limited set of observed examples. Current CZSL methodologies, despite their advancements, tend to neglect the distinct... 详细信息
来源: 评论
CapsuleRRT: Relationships-aware Regression Tracking via Capsules
CapsuleRRT: Relationships-aware Regression Tracking via Caps...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Ma, Ding Wu, Xiangqian Harbin Inst Technol Sch Comp Sci & Technol Harbin Peoples R China
Regression tracking has gained more and more attention thanks to its easy-to-implement characteristics, while existing regression trackers rarely consider the relationships between the object parts and the complete ob... 详细信息
来源: 评论