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Ziwei Yu Linlin Yang You Xie Ping Chen Angela Yao

Abstract
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.
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| 3d-hand-pose-estimation-on-ho-3d-v3 | Yu et al. | PA-MPJPE: 10.8 PA-MPVPE: 10.4 |
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