metadata

license: cc-by-nc-4.0
language:
  - zh
tags:
  - sign-language

Summary

This is the dataset proposed in our paper "Uni-Sign: Toward Unified Sign Language Understanding at Scale". CSL-News is a large-scale Chinese Sign Language dataset designed for developing robust sign language understanding models.

Code: https://github.com/ZechengLi19/Uni-Sign

Download

Please refer to download script to download CSL_News. You can also download each file by wget, for instance:

wget https://huggingface.co/datasets/ZechengLi19/CSL-News/resolve/main/archive_001.zip
wget https://huggingface.co/datasets/ZechengLi19/CSL-News/resolve/main/archive_002.zip
wget https://huggingface.co/datasets/ZechengLi19/CSL-News/resolve/main/archive_003.zip
...

Usage

You can unzip each archive_*.zip file by unzip, for instance:

unzip -j archive_001.zip -d ./CSL_News/rgb_format
unzip -j archive_002.zip -d ./CSL_News/rgb_format
unzip -j archive_003.zip -d ./CSL_News/rgb_format
...

CSL_News_Labels.json and CSL_News_Labels.csv contains the text-annotations for CSL-News. They can easily be read by

# Read CSL_News_Labels.json
import json
with open('CSL_News_Labels.json', 'r', encoding='utf-8') as f:
    data = json.load(f)
# Read CSL_News_Labels.csv
import pandas
data = pandas.read_csv("CSL_News_Labels.csv")

Other format

We also provide the CSL-News dataset in a pose format. Please refer to here.

License

CSL-News is released under the CC-BY-NC-4.0 license. The video samples in this dataset are collected from publicly available web videos. Users must ensure that their use of these video samples is strictly non-commercial.

Why Non-Commercial?

The video samples in CSL-News are sourced from web videos, and their copyright belongs to the original content creators. While this dataset is provided for research purposes under the CC-BY-NC-4.0 license, commercial use of these videos may infringe upon the rights of the original creators. To respect their rights and ensure ethical use, we strictly enforce a non-commercial usage policy for CSL-News.

Citation

@article{li2025uni-sign,
  title={Uni-Sign: Toward Unified Sign Language Understanding at Scale},
  author={Li, Zecheng and Zhou, Wengang and Zhao, Weichao and Wu, Kepeng and Hu, Hezhen and Li, Houqiang},
  journal={arXiv preprint arXiv:2501.15187},
  year={2025}
}