{
 "id": "kr-cen/VidLayer",
 "owner": "kr-cen",
 "name": "VidLayer",
 "downloads": 4775,
 "likes": 5,
 "last_modified": "2026-07-19T16:55:45.000Z",
 "stated_licence": "apache-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-to-video"
 ],
 "citation": "If you find this dataset or the associated work useful for your research, please cite the paper:\n\n```bib\n@article{li2025layert2v,\n  title={LayerT2V: A Unified Multi-Layer Video Generation Framework},\n  author={Li, Guangzhao and Cen, Kangrui and Zhao, Baixuan and Xin, Yi and Luo, Siqi and Zhai, Guangtao and Zhang, Lei and Liu, Xiaohong},\n  journal={arXiv e-prints},\n  pages={arXiv--2508},\n  year={2025}\n}\n```",
 "signal": "permissive",
 "reason": "The declared licence (apache-2.0) is classified as permissive.",
 "revision": "2618213d0d7a458c82d0b2ef5c61fd93ddab1f37",
 "stated_evidence": "https://huggingface.co/datasets/kr-cen/VidLayer/blob/2618213d0d7a458c82d0b2ef5c61fd93ddab1f37/README.md",
 "file_evidence": "https://huggingface.co/datasets/kr-cen/VidLayer/tree/2618213d0d7a458c82d0b2ef5c61fd93ddab1f37",
 "card_nc": false
}