Skip to content

Latest commit

 

History

History
76 lines (65 loc) · 3.65 KB

README.md

File metadata and controls

76 lines (65 loc) · 3.65 KB

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

Zhengdi Yu1,2 · Shaoli Huang2 · Yongkang Cheng2 · Tolga Birdal1

1Imperial College London, 2Tencent AI Lab

Logo


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

Blender Blender
SLP from HamNoSys SLP from Word
Blender Blender
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 [email protected]