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Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur

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发表于 2025-3-21 19:10:03 | 显示全部楼层 |阅读模式
书目名称Computer Vision – ECCV 2020
副标题16th European Confer
编辑Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm
视频videohttp://file.papertrans.cn/235/234221/234221.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur
描述The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic..The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 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 2020
关键词computer networks; computer vision; Human-Computer Interaction (HCI); image coding; image processing; ima
版次1
doihttps://doi.org/10.1007/978-3-030-58545-7
isbn_softcover978-3-030-58544-0
isbn_ebook978-3-030-58545-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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AUTO3D: Novel View Synthesis Through Unsupervisely Learned Variational Viewpoint and Global 3D Reprhe relative-pose in a prior distribution. In various applications, we demonstrate that our model can achieve comparable or even better results than pose/3D model-supervised learning-based novel view synthesis (NVS) methods with any number of input views.
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Soft Anchor-Point Object Detection,evels, respectively. To evaluate the effectiveness, we train a single-stage anchor-free detector called Soft Anchor-Point Detector (SAPD). Experiments show that our concise SAPD pushes the envelope of speed/accuracy trade-off to a new level, outperforming recent state-of-the-art anchor-free and anch
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Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid, the output layers for the task of object mask annotation, and show that reasoning about object boundaries on our predicted polygonal grid leads to more accurate results over existing pixel-wise and curve-based approaches. We finally showcase . as a standalone module for unsupervised image partition
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Joint Learning of Social Groups, Individuals Action and Sub-group Activities in Videos,-of-the-art results on two widely adopted benchmarks for the traditional group activity recognition task (assuming individuals of the scene form a single group and predicting a single group activity label for the scene); iii) we introduce new annotations on an existing group activity dataset, re-pur
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Relative Pose Estimation of Calibrated Cameras with Known , Invariants,ion constrained by . invariants, we also present a comprehensive study of existing polynomial formulations for relative pose estimation and discover their relationship. Different formulations are carefully chosen for each proposed problems to achieve best efficiency. Experiments on synthetic and rea
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