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检索条件"任意字段=2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024"
11890 条 记 录,以下是271-280 订阅
排序:
Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation
Boosting Object Detection with Zero-Shot Day-Night Domain Ad...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Du, Zhipeng Shi, Miaojing Deng, Jiankang Kings Coll London Dept Informat London England Tongji Univ Coll Elect & Informat Engn Shanghai Peoples R China Imperial Coll London Dept Comp London England Huawei London Res London England
Detecting objects in low-light scenarios presents a persistent challenge, as detectors trained on well-lit data exhibit significant performance degradation on low-light data due to low visibility. Previous methods mit... 详细信息
来源: 评论
DeCoTR: Enhancing Depth Completion with 2D and 3D Attentions
DeCoTR: Enhancing Depth Completion with 2D and 3D Attentions
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Shi, Yunxiao Singh, Manish Kumar Cai, Hong Porikli, Fatih Qualcomm AI Res San Diego CA 92121 USA
In this paper, we introduce a novel approach that harnesses both 2D and 3D attentions to enable highly accurate depth completion without requiring iterative spatial propagations. Specifically, we first enhance a basel... 详细信息
来源: 评论
GenZI: Zero-Shot 3D Human-Scene Interaction Generation
GenZI: Zero-Shot 3D Human-Scene Interaction Generation
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Li, Lei Dai, Angela Tech Univ Munich Munich Germany
Can we synthesize 3D humans interacting with scenes without learning from any 3D human-scene interaction data? We propose GenZI(1), the first zero-shot approach to generating 3D human-scene interactions. Key to GenZI ... 详细信息
来源: 评论
CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation
CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Inter...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Chowdhury, Townim Faisal Liao, Kewen Vu Minh Hieu Phan To, Minh-Son Xie, Yutong Hung, Kevin Rose, David van den Hengel, Anton Verjans, Johan W. Liao, Zhibin Univ Adelaide Australian Inst Machine Learning Adelaide SA Australia Australian Catholic Univ Fitzroy Vic Australia Flinders Univ S Australia Adelaide SA Australia Cent Adelaide Local Hlth Network SA Pathol Adelaide SA Australia
Deep Neural Networks (DNNs) are widely used for visual classification tasks, but their complex computation process and black-box nature hinder decision transparency and interpretability. Class activation maps (CAMs) a... 详细信息
来源: 评论
VideoCon: Robust Video-Language Alignment via Contrast Captions
VideoCon: Robust Video-Language Alignment via Contrast Capti...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Bansall, Hritik Bitton, Yonatan Szpektor, Idan Chang, Kai-Wei Grover, Aditya UCLA Los Angeles CA 90095 USA Google Res Mountain View CA USA
Despite being (pre)trained on a massive amount of data, state-of-the-art video-language alignment models are not robust to semantically-plausible contrastive changes in the video captions. Our work addresses this by i... 详细信息
来源: 评论
Multiscale vision Transformers meet Bipartite Matching for efficient single-stage Action Localization
Multiscale Vision Transformers meet Bipartite Matching for e...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Ntinou, Ioanna Sanchez, Enrique Tzimiropoulos, Georgios Queen Mary Univ London London England Samsung AI Ctr Cambridge Cambridge England
Action Localization is a challenging problem that combines detection and recognition tasks, which are often addressed separately. State-of-the-art methods rely on off-the-shelf bounding box detections pre-computed at ... 详细信息
来源: 评论
Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained vision Transfomers
Not All Prompts Are Secure: A Switchable Backdoor Attack Aga...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Yang, Sheng Bai, Jiawang Gao, Kuofeng Yang, Yong Li, Yiming Xia, Shu-Tao Tsinghua Univ Beijing Peoples R China Tencent Secur Platform Dept Shenzhen Peoples R China Zhejiang Univ Hangzhou Peoples R China Peng Cheng Lab Res Ctr Artificial Intelligence Shenzhen Peoples R China
Given the power of vision transformers, a new learning paradigm, pretraining and then prompting, makes it more efficient and effective to address downstream visual recognition tasks. In this paper, we identify a novel... 详细信息
来源: 评论
Holo-Relighting: Controllable Volumetric Portrait Relighting from a Single Image
Holo-Relighting: Controllable Volumetric Portrait Relighting...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Mei, Yiqun Zeng, Yu Zhang, He Shu, Zhixin Zhang, Xuaner Bi, Sai Zhang, Jianming Jung, HyunJoon Patel, Vishal M. Johns Hopkins Univ Baltimore MD 21218 USA Adobe Inc San Jose CA USA
At the core of portrait photography is the search for ideal lighting and viewpoint. The process often requires advanced knowledge in photography and an elaborate studio setup. In this work, we propose Holo-Relighting,... 详细信息
来源: 评论
AffordanceLLM: Grounding Affordance from vision Language Models
AffordanceLLM: Grounding Affordance from Vision Language Mod...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Qian, Shengyi Chen, Weifeng Bai, Mm Zhou, Xiong Tu, Zhuowen Li, Li Erran Amazon AWS AI Seattle WA 98109 USA
Affordance grounding refers to the task of finding the area of an object with which one can interact. It is a fundamental but challenging task, as a successful solution requires the comprehensive understanding of a sc... 详细信息
来源: 评论
TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understanding
TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Liu, Yun Yang, Haolin Si, Xu Liu, Ling Li, Zipeng Zhang, Yuxiang Liu, Yebin Yi, Li Tsinghua Univ Beijing Peoples R China Shanghai Artificial Intelligence Lab Shanghai Peoples R China Shanghai Qi Zhi Inst Shanghai Peoples R China Beijing Univ Posts & Telecommun Beijing Peoples R China Beijing Inst Technol Beijing Peoples R China
Humans commonly work with multiple objects in daily life and can intuitively transfer manipulation skills to novel objects by understanding object functional regularities. However, existing technical approaches for an... 详细信息
来源: 评论