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

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書目名稱Computer Vision – ECCV 2020影響因子(影響力)




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書目名稱Computer Vision – ECCV 2020讀者反饋學(xué)科排名

Tdd526

octogenarian

加強(qiáng)防衛(wèi)

Simplicial Complex Based Point Correspondence Between Images Warped onto Manifolds,cess of higher-order assignment methods, has sparked an interest in the search for improved higher-order matching algorithms on warped images due to projection. Although, currently, several existing methods “flatten” such 3D images to use planar graph/hypergraph matching methods, they still suffer f

啞巴

dura-mater

Distance-Normalized Unified Representation for Monocular 3D Object Detection,bject detection, we introduce a single-stage and multi-scale framework to learn a unified representation for objects within different distance ranges, termed as UR3D. UR3D formulates different tasks of detection by exploiting the scale information, to reduce model capacity requirement and achieve ac

dura-mater

黑豹

Where to Explore Next? ExHistCNN for History-Aware Autonomous 3D Exploration,imation of the Next Best View (NBV) that maximises the coverage of the unknown area. We do this by re-formulating NBV estimation as a classification problem and we propose a novel learning-based metric that encodes both, the current 3D observation (a depth frame) and the history of the ongoing recon

ALOFT

Semi-supervised Segmentation Based on Error-Correcting Supervision,oped recently. In this work, we augment such supervised segmentation models by allowing them to learn from unlabeled data. Our semi-supervised approach, termed Error-Correcting Supervision, leverages a collaborative strategy. Apart from the supervised training on the labeled data, the segmentation n

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