Dual Grid Net: Hand Mesh Vertex Regression from Single Depth Maps

Chengde Wan; Thomas Probst; Luc Van Gool; Angela Yao

ECCV 2020poster31 citations

Dual Grid Net: Hand Mesh Vertex Regression from Single Depth Maps

Chengde Wan, Thomas Probst, Luc Van Gool, Angela Yao

Abstract

We aim to recover the dense 3D surface of the hand from depth maps and propose a network that can predict mesh vertices, transformation matrices for every joint and joint coordinates in a single forward pass. Use fully convolutional architectures, we first map depth image features to the mesh grid and then regress the mesh coordinates into real world 3D coordinates. The final mesh is found by sampling from the mesh grid refit in closed-form based on an articulated template mesh.

BibTeX

@inproceedings{eccv2020_dualgridnethandm,
  title = {Dual Grid Net: Hand Mesh Vertex Regression from Single Depth Maps},
  author = {Chengde Wan and Thomas Probst and Luc Van Gool and Angela Yao},
  booktitle = {ECCV 2020},
  year = {2020}
}