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Self-learning Canonical Space for Multi-view 3D Human Pose Estimation
March 20, 2024, 4:45 a.m. | Xiaoben Li, Mancheng Meng, Ziyan Wu, Terrence Chen, Fan Yang, Dinggang Shen
cs.CV updates on arXiv.org arxiv.org
Abstract: Multi-view 3D human pose estimation is naturally superior to single view one, benefiting from more comprehensive information provided by images of multiple views. The information includes camera poses, 2D/3D human poses, and 3D geometry. However, the accurate annotation of these information is hard to obtain, making it challenging to predict accurate 3D human pose from multi-view images. To deal with this issue, we propose a fully self-supervised framework, named cascaded multi-view aggregating network (CMANet), to …
abstract annotation arxiv canonical cs.cv geometry however human images information making multiple self-learning space the information type view
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