Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars

• URL: http://arxiv.org/abs/2410.08840v1
• Date: Fri, 11 Oct 2024 14:14:51 GMT
• Title: Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars
• Authors: Xuan Huang, Hanhui Li, Wanquan Liu, Xiaodan Liang, Yiqiang Yan, Yuhao Cheng, Chengqiang Gao,
• Abstract summary: We propose to create animatable avatars for interacting hands with 3D Gaussian Splatting (GS) and single-image inputs. Our proposed method is validated via extensive experiments on the large-scale InterHand2.6M dataset.
• Score: 47.61442517627826
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose to create animatable avatars for interacting hands with 3D Gaussian Splatting (GS) and single-image inputs. Existing GS-based methods designed for single subjects often yield unsatisfactory results due to limited input views, various hand poses, and occlusions. To address these challenges, we introduce a novel two-stage interaction-aware GS framework that exploits cross-subject hand priors and refines 3D Gaussians in interacting areas. Particularly, to handle hand variations, we disentangle the 3D presentation of hands into optimization-based identity maps and learning-based latent geometric features and neural texture maps. Learning-based features are captured by trained networks to provide reliable priors for poses, shapes, and textures, while optimization-based identity maps enable efficient one-shot fitting of out-of-distribution hands. Furthermore, we devise an interaction-aware attention module and a self-adaptive Gaussian refinement module. These modules enhance image rendering quality in areas with intra- and inter-hand interactions, overcoming the limitations of existing GS-based methods. Our proposed method is validated via extensive experiments on the large-scale InterHand2.6M dataset, and it significantly improves the state-of-the-art performance in image quality. Project Page: \url{https://github.com/XuanHuang0/GuassianHand}.

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