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UV-Based 3D Hand-Object Reconstruction with Grasp Optimization

About

We propose a novel framework for 3D hand shape reconstruction and hand-object grasp optimization from a single RGB image. The representation of hand-object contact regions is critical for accurate reconstructions. Instead of approximating the contact regions with sparse points, as in previous works, we propose a dense representation in the form of a UV coordinate map. Furthermore, we introduce inference-time optimization to fine-tune the grasp and improve interactions between the hand and the object. Our pipeline increases hand shape reconstruction accuracy and produces a vibrant hand texture. Experiments on datasets such as Ho3D, FreiHAND, and DexYCB reveal that our proposed method outperforms the state-of-the-art.

Ziwei Yu, Linlin Yang, You Xie, Ping Chen, Angela Yao• 2022

Related benchmarks

TaskDatasetResultRank
3D Hand ReconstructionFreiHAND
PA MPVPE0.73
20
3D Hand ReconstructionHO3D v3
PA-MPJPE10.8
18
3D Hand-Object ReconstructionHO3D v2
MPJPE1.04
11
3D Hand-Object ReconstructionHO3D v3
MPJPE1.08
10
3D Mesh ReconstructionHO3D v3
PA-MPJPE10.8
9
3D Hand-Object ReconstructionDexYCB (S0)
MPJPE1.09
8
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