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This paper focuses on the incorporation of kinematic constraints with the learning of 3D skeleton reconstruction without suffering from corrupted pose estimations. Specifically, we devote to exploring ...
Graph convolutional networks (GCNs) are the most commonly used methods for skeleton-based action recognition and have achieved remarkable performance. Generating adjacency matrices with semantically ...