SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark

Zhengdi Yu^1,2 · Shaoli Huang² · Yongkang Cheng² · Tolga Birdal¹

¹Imperial College London, ²Tencent AI Lab

SignAvatars is the first large-scale 3D sign language holistic motion dataset with mesh annotations, which comprises 8.34M precise 3D whole-body SMPL-X annotations, covering 70K motion sequences. The corresponding MANO hand version is also provided.

News 🚩

[2023/11/2] Paper is now available. ⭐

Dataset description

Dataset download

Coming soon!

Application examples on SLP


SLP from HamNoSys	SLP from Word

SLP from ASL	SLP from GSL

Instruction

Coming soon!

Citation

@inproceedings{yu2023signavatars,
  title = {SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark},
  author = {Yu, Zhengdi and Huang, Shaoli and Cheng, Yongkakng and Birdal, Tolga},
  journal = {arXiv preprint arXiv:2310.20436},
  month     = {November},
  year      = {2023}
  }

Contact

For technical questions, please contact ZhengdiYu@hotmail.com

cyk990422/SignAvatars