SignAvatars
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(ECCV 2024) SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark
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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
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 :triangular_flag_on_post:
- [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 [email protected]