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检索条件"任意字段=2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023"
11753 条 记 录,以下是261-270 订阅
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MAP: Multimodal Uncertainty-Aware vision-Language Pre-training Model
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-traini...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Ji, Yatai Wang, Junjie Gong, Yuan Zhang, Lin Zhu, Yanru Wang, Hongfa Zhang, Jiaxing Sakai, Tetsuya Yang, Yujiu Tsinghua Univ Beijing Peoples R China Waseda Univ Tokyo Japan IDEA Gandhinagar India Tencent TEG Shenzhen Peoples R China
Multimodal semantic understanding often has to deal with uncertainty, which means the obtained messages tend to refer to multiple targets. Such uncertainty is problematic for our interpretation, including inter- and i... 详细信息
来源: 评论
Angelic Patches for Improving Third-Party Object Detector Performance
Angelic Patches for Improving Third-Party Object Detector Pe...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Si, Wenwen Li, Shuo Park, Sangdon Lee, Insup Bastani, Osbert Univ Penn Dept Comp & Info Sci Philadelphia PA 19104 USA Georgia Inst Technol Sch Cybersecur & Privacy Atlanta GA 30332 USA
Deep learning models have shown extreme vulnerability to distribution shifts such as synthetic perturbations and spatial transformations. In this work, we explore whether we can adopt the characteristics of adversaria... 详细信息
来源: 评论
Train-Once-for-All Personalization
Train-Once-for-All Personalization
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Chen, Hong-You Li, Yandong Cui, Yin Zhang, Mingda Chao, Wei-Lun Zhang, Li Ohio State Univ Columbus OH 43210 USA Google Res Mountain View CA 94043 USA
We study the problem of how to train a "personalization-friendly" model such that given only the task descriptions, the model can be adapted to different end-users' needs, e.g., for accurately classifyin... 详细信息
来源: 评论
Learning Discriminative Representations for Skeleton Based Action recognition
Learning Discriminative Representations for Skeleton Based A...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Zhou, Huanyu Liu, Qingjie Wang, Yunhong Beihang Univ State Key Lab Virtual Real Technol & Syst Beijing Peoples R China Zhongguancun Lab Beijing Peoples R China Beihang Univ Hangzhou Innovat Inst Beijing Peoples R China
Human action recognition aims at classifying the category of human action from a segment of a video. Recently, people have dived into designing GCN-based models to extract features from skeletons for performing this t... 详细信息
来源: 评论
Dynamic Inference with Grounding Based vision and Language Models
Dynamic Inference with Grounding Based Vision and Language M...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Uzkent, Burak Garg, Amanmeet Zhu, Wentao Doshi, Keval Yi, Jingru Wang, Xiaolong Omar, Mohamed Amazon Prime Video Seattle WA 30439 USA
Transformers have been recently utilized for vision and language tasks successfully. For example, recent image and language models with more than 200M parameters have been proposed to learn visual grounding in the pre... 详细信息
来源: 评论
Unbalanced Optimal Transport: A Unified Framework for Object Detection
Unbalanced Optimal Transport: A Unified Framework for Object...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: De Plaen, Henri De Plaen, Pierre-Francois Suykens, Johan A. K. Proesmans, Marc Tuytelaars, Tinne Van Gool, Luc Katholieke Univ Leuven ESAT STADIUS Leuven Belgium Katholieke Univ Leuven ESAT PSI Leuven Belgium Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland
During training, supervised object detection tries to correctly match the predicted bounding boxes and associated classification scores to the ground truth. This is essential to determine which predictions are to be p... 详细信息
来源: 评论
Real-time 6K Image Rescaling with Rate-distortion Optimization
Real-time 6K Image Rescaling with Rate-distortion Optimizati...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Qi, Chenyang Yang, Xin Cheng, Ka Leong Chen, Ying-Cong Chen, Qifeng Hong Kong Univ Sci & Technol Hong Kong Peoples R China
Contemporary image rescaling aims at embedding a high-resolution (HR) image into a low-resolution (LR) thumbnail image that contains embedded information for HR image reconstruction. Unlike traditional image super-res... 详细信息
来源: 评论
DepGraph: Towards Any Structural Pruning
DepGraph: Towards Any Structural Pruning
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Fang, Gongfan Ma, Xinyin Song, Mingli Mi, Michael Bi Wang, Xinchao Natl Univ Singapore Singapore Singapore Zhejiang Univ Hangzhou Peoples R China Huawei Technol Ltd Shenzhen Peoples R China
Structural pruning enables model acceleration by removing structurally-grouped parameters from neural networks. However, the parameter-grouping patterns vary widely across different models, making architecture-specifi... 详细信息
来源: 评论
Learning Customized Visual Models with Retrieval-Augmented Knowledge
Learning Customized Visual Models with Retrieval-Augmented K...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Liu, Haotian Son, Kilho Yang, Jianwei Liu, Ce Gao, Jianfeng Lee, Yong Jae Li, Chunyuan Univ Wisconsin Madison Madison WI 53706 USA Microsoft Redmond WA USA
Image-text contrastive learning models such as CLIP have demonstrated strong task transfer ability. The high generality and usability of these visual models is achieved via a web-scale data collection process to ensur... 详细信息
来源: 评论
Physics-Guided ISO-Dependent Sensor Noise Modeling for Extreme Low-Light Photography
Physics-Guided ISO-Dependent Sensor Noise Modeling for Extre...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Cao, Yue Liu, Ming Liu, Shuai Wang, Xiaotao Lei, Lei Zuo, Wangmeng Harbin Inst Technol Sch Comp Sci & Technol Harbin Peoples R China Peng Cheng Lab Shenzhen Peoples R China
Although deep neural networks have achieved astonishing performance in many vision tasks, existing learning-based methods are far inferior to the physical model-based solutions in extreme low-light sensor noise modeli... 详细信息
来源: 评论