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EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devices. (arXiv:2112.07642v3 [cs.CV] UPDATED)
Aug. 17, 2022, 1:12 a.m. | Siwei Zhang, Qianli Ma, Yan Zhang, Zhiyin Qian, Taein Kwon, Marc Pollefeys, Federica Bogo, Siyu Tang
cs.CV updates on arXiv.org arxiv.org
Understanding social interactions from egocentric views is crucial for many
applications, ranging from assistive robotics to AR/VR. Key to reasoning about
interactions is to understand the body pose and motion of the interaction
partner from the egocentric view. However, research in this area is severely
hindered by the lack of datasets. Existing datasets are limited in terms of
either size, capture/annotation modalities, ground-truth quality, or
interaction diversity. We fill this gap by proposing EgoBody, a novel
large-scale dataset for human …
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