Motion Guided 3D Pose Estimation from Videos

european conference on computer vision, pp. 764-780, 2020.

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We trained our model on 2D poses predicted by cascaded pyramid network

Abstract:

We propose a new loss function, called motion loss, for the problem of monocular 3D Human pose estimation from 2D pose. In computing motion loss, a simple yet effective representation for keypoint motion, called pairwise motion encoding, is introduced. We design a new graph convolutional network architecture, U-shaped GCN (UGCN). It cap...More

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