OHTA: One-shot Hand Avatar via Data-driven Implicit Priors

Xiaozheng Zheng^*  Chao Wen^*  Zhuo Su  Zeran Xu  Zhaohu Li  Yang Zhao  Zhou Xue^† 

PICO, ByteDance

^*Equal contribution   ^†Corresponding author

🤩 Accepted to CVPR 2024

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OHTA is a novel approach capable of creating implicit animatable hand avatars using just a single image. It facilitates 1) text-to-avatar conversion, 2) hand texture and geometry editing, and 3) interpolation and sampling within the latent space.

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📣 Updates

[02/2024] 🥳 OHTA is accepted to CVPR 2024! Working on code release!

🤟 Citation

If you find our work useful for your research, please consider citing the paper:

@inproceedings{
  zheng2024ohta,
  title={OHTA: One-shot Hand Avatar via Data-driven Implicit Priors},
  author={Zheng, Xiaozheng and Wen, Chao and Zhuo, Su and Xu, Zeran and Li, Zhaohu and Zhao, Yang and Xue, Zhou},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2024}
}

🗞️ License

Distributed under the MIT License. See LICENSE for more information.