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Joint 3D Human Shape Recovery and Pose Estimation from a Single Image with Bilayer Graph
[article]
2021
arXiv
pre-print
The ability to estimate the 3D human shape and pose from images can be useful in many contexts. Recent approaches have explored using graph convolutional networks and achieved promising results. The fact that the 3D shape is represented by a mesh, an undirected graph, makes graph convolutional networks a natural fit for this problem. However, graph convolutional networks have limited representation power. Information from nodes in the graph is passed to connected neighbors, and propagation of
arXiv:2110.08472v2
fatcat:mnhfcnawsrdyhktfpdltavi7sq