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Occluded Human Body Capture with Self-Supervised Spatial-Temporal Motion Prior
[article]
2022
arXiv
pre-print
Although significant progress has been achieved on monocular maker-less human motion capture in recent years, it is still hard for state-of-the-art methods to obtain satisfactory results in occlusion scenarios. There are two main reasons: the one is that the occluded motion capture is inherently ambiguous as various 3D poses can map to the same 2D observations, which always results in an unreliable estimation. The other is that no sufficient occluded human data can be used for training a robust
arXiv:2207.05375v1
fatcat:qdhdmpfyhrd3ljjkqrcialgzxq