--- title: ChronoMagic Bench emoji: 🥇 colorFrom: green colorTo: indigo sdk: gradio app_file: app.py license: apache-2.0 sdk_version: 5.31.0 short_description: A Benchmark for Metamorphic Evaluation of T2V Generation thumbnail: >- https://cdn-uploads.huggingface.co/production/uploads/63468720dd6d90d82ccf3450/3DHmAAzSsKWiGRYMY7bWu.jpeg ---

[NeurIPS D&B 2024 Spotlight] ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation

If you like our project, please give us a star ⭐ on GitHub for the latest update.
## 💡 Description - **Repository:** [Code](https://github.com/PKU-YuanGroup/ChronoMagic-Bench), [Page](https://pku-yuangroup.github.io/ChronoMagic-Bench/), [Data](https://huggingface.co/collections/BestWishYsh/chronomagic-bench-667bea7abfe251ebedd5b8dd) - **Paper:** [https://huggingface.co/papers/2406.18522](https://huggingface.co/papers/2406.18522) - **Point of Contact:** [Shenghai Yuan](shyuan-cs@hotmail.com) ## ✏️ Citation If you find our paper and code useful in your research, please consider giving a star and citation. ```BibTeX @article{yuan2024chronomagic, title={Chronomagic-bench: A benchmark for metamorphic evaluation of text-to-time-lapse video generation}, author={Yuan, Shenghai and Huang, Jinfa and Xu, Yongqi and Liu, Yaoyang and Zhang, Shaofeng and Shi, Yujun and Zhu, Rui-Jie and Cheng, Xinhua and Luo, Jiebo and Yuan, Li}, journal={Advances in Neural Information Processing Systems}, volume={37}, pages={21236--21270}, year={2024} } ```