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Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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发表于 2025-3-21 20:03:46 | 显示全部楼层 |阅读模式
书目名称Computer Vision – ECCV 2022
副标题17th European Confer
编辑Shai Avidan,Gabriel Brostow,Tal Hassner
视频videohttp://file.papertrans.cn/235/234277/234277.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app
描述The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022..The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation..
出版日期Conference proceedings 2022
关键词artificial intelligence; computer networks; computer systems; computer vision; education; Human-Computer
版次1
doihttps://doi.org/10.1007/978-3-031-19769-7
isbn_softcover978-3-031-19768-0
isbn_ebook978-3-031-19769-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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,Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World,is task have shown great success on synthetic datasets, we have observed them to fail in the presence of real-world data. We thus analyze the causes of these failures, which we trace back to the difference between the feature distributions of the source and target point clouds, and the sensitivity o
发表于 2025-3-22 01:05:36 | 显示全部楼层
,An End-to-End Transformer Model for Crowd Localization,oxes or pre-designed localization maps, relying on complex post-processing to obtain the head positions. In this paper, we propose an elegant, end-to-end .rowd .ocalization .ansformer named CLTR that solves the task in the regression-based paradigm. The proposed method views the crowd localization a
发表于 2025-3-22 06:50:31 | 显示全部楼层
,Few-Shot Single-View 3D Reconstruction with Memory Prior Contrastive Network,revious approaches mainly focus on how to design shape prior models for different categories. Their performance on unseen categories is not very competitive. In this paper, we present a Memory Prior Contrastive Network (MPCN) that can store shape prior knowledge in a few-shot learning based 3D recon
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