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Titlebook: Computer Vision – ACCV 2020 Workshops; 15th Asian Conferenc Imari Sato,Bohyung Han Conference proceedings 2021 Springer Nature Switzerland

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21#
發(fā)表于 2025-3-25 04:56:25 | 只看該作者
22#
發(fā)表于 2025-3-25 11:07:55 | 只看該作者
23#
發(fā)表于 2025-3-25 14:10:36 | 只看該作者
Eljar Akhgarnush,Fabian Bruse,Ben Hofertions should robustly estimate the jaywalking pedestrians. However, the task of robustly estimating jaywalking is not trivial, especially in the case of visible camera-based estimation. In this work, a two-step hierarchical deep learning formulation using visible and thermal camera is proposed to ad
24#
發(fā)表于 2025-3-25 17:55:22 | 只看該作者
Lars Rautenburger,Alexander Lieblm is the example-based approach. The existing example-based approaches often calculate a global pose error to search a single match 3D pose from the source library. This way fails to capture the local deformations of human pose and highly dependent on a large training set. To alleviate these issues,
25#
發(fā)表于 2025-3-25 20:32:54 | 只看該作者
Processes in a Digital Environment is applied to a facial video, the detected landmarks occasionally jitter, whereas the face apparently does not move. We hypothesize that there are two causes that induce the unstable detection: (1) small changes in input images and (2) inconsistent annotations. Corresponding to the causes, we propo
26#
發(fā)表于 2025-3-26 03:37:02 | 只看該作者
27#
發(fā)表于 2025-3-26 04:21:40 | 只看該作者
28#
發(fā)表于 2025-3-26 12:22:50 | 只看該作者
Conference proceedings 2021h was held in Kyoto, Japan, in November/ December 2020.*.The 13 papers were carefully reviewed and selected from the following two workshops: Machine Learning and Computing for Visual Semantic Analysis (MLCSA) and Multi-Visual-Modality Human Activity Understanding (MMHAU)..*The conference and workshops were held virtually..
29#
發(fā)表于 2025-3-26 14:47:32 | 只看該作者
30#
發(fā)表于 2025-3-26 19:44:41 | 只看該作者
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