Multi-person 3D pose estimation from unlabelled data

Its numerous applications make multi-human 3D pose estimation a remarkably impactful area of research. Nevertheless, it presents several challenges, especially when approached using multiple views and regular RGB cameras as the only input. First, each person must be uniquely identified in the differ...

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Bibliographic Details

Main Authors:	Daniel Rodriguez-Criado, Pilar Bachiller-Burgos, George Vogiatzis, Luis J.Manso
Format:	Default Article
Published:	2024
Subjects:	Engineering Information and computing sciences Theory of computation Cognitive and computational psychology 3D multi-pose estimation Skeleton matching Deep learning Graph neural networks Self-supervised learning
Online Access:	https://hdl.handle.net/2134/26484682.v1
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