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Found 2 papers, 2 papers with code
Spatio-temporal MLP-graph network for 3D human pose estimation
Graph convolutional networks and their variants have shown significant promise in 3D human pose estimation.
Regular Splitting Graph Network for 3D Human Pose Estimation
In human pose estimation methods based on graph convolutional architectures, the human skeleton is usually modeled as an undirected graph whose nodes are body joints and edges are connections between neighboring joints.
Ranked #40 on
3D Human Pose Estimation
on MPI-INF-3DHP
(AUC metric)
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