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license: apache-2.0 |
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## Latte: Latent Diffusion Transformer for Video Generation |
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This repo contains text-to-video generation pre-trained weights for our paper exploring latent diffusion models with transformers (Latte). You can find more visualizations on our [project page](https://maxin-cn.github.io/latte_project/). |
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If you want to obtain pre-trained weights on FaceForensics, SkyTimelapse, UCF101, and Taichi-HD, please refer to [here](https://huggingface.co/maxin-cn/Latte). |
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## News |
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- (π₯ New) May. 23, 2024. π₯ **Latte-1** for Text-to-video generation is released! You can download pre-trained model [here](https://huggingface.co/maxin-cn/LatteT2V/tree/main/transformer_v1). Latte-1 also supports Text-to-image generation, please run bash sample/t2i.sh. |
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- (π₯ New) Mar. 20, 2024. π₯ An updated LatteT2V model is coming soon, stay tuned! |
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- (π₯ New) Feb. 24, 2024. π₯ We are very grateful that researchers and developers like our work. We will continue to update our LatteT2V model, hoping that our efforts can help the community develop. Our Latte [discord](https://discord.gg/RguYqhVU92) channel is created for discussions. Coders are welcome to contribute. |
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- (π₯ New) Jan. 9, 2024. π₯ An updated LatteT2V model initialized with the [PixArt-Ξ±](https://github.com/PixArt-alpha/PixArt-alpha) is released, the checkpoint can be found [here](https://huggingface.co/maxin-cn/LatteT2V/tree/main/transformer). |
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- (π₯ New) Oct. 31, 2023. π₯ The training and inference code is released. All checkpoints (including FaceForensics, SkyTimelapse, UCF101, and Taichi-HD) can be found [here](https://huggingface.co/maxin-cn/Latte/tree/main). In addition, the LatteT2V inference code is provided. |
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## Contact Us |
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**Yaohui Wang**: [wangyaohui@pjlab.org.cn](mailto:wangyaohui@pjlab.org.cn) |
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**Xin Ma**: [xin.ma1@monash.edu](mailto:xin.ma1@monash.edu) |
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## Citation |
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If you find this work useful for your research, please consider citing it. |
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```bibtex |
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@article{ma2024latte, |
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title={Latte: Latent Diffusion Transformer for Video Generation}, |
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author={Ma, Xin and Wang, Yaohui and Jia, Gengyun and Chen, Xinyuan and Liu, Ziwei and Li, Yuan-Fang and Chen, Cunjian and Qiao, Yu}, |
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journal={arXiv preprint arXiv:2401.03048}, |
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year={2024} |
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} |
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``` |
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## Acknowledgments |
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Latte has been greatly inspired by the following amazing works and teams: [DiT](https://github.com/facebookresearch/DiT) and [PixArt-Ξ±](https://github.com/PixArt-alpha/PixArt-alpha), we thank all the contributors for open-sourcing. |
