--- license: creativeml-openrail-m language: - en library_name: diffusers pipeline_tag: text-to-video tags: - AIGC - text2video - image2video - infinite-length - human --- # MuseV MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Parallel Denoising
Zhiqiang Xia \*, Zhaokang Chen\*, Bin Wu, Chao Li, Kwok-Wai Hung, Chao Zhan, Wenjiang Zhou (*co-first author, Corresponding Author)
**[project](comming soon)** **Technical report (comming soon)** We have setup the world simulator vision since March 2023, believing diffusion models can simulate the world. `MuseV` was a milestone achieved around July 2023. Amazed by the progress of Sora, we decided to opensource `MuseV`, hopefully it will benefit the community. Our next move will switch to the promising diffusion+transformer scheme. Please stay tuned. We will soon release `MuseTalk`, a diffusion-baesd lip sync model, which can be applied with MuseV as a complete virtual human generation solution. Please stay tuned! # Intro `MuseV` is a diffusion-based virtual human video generation framework, which 1. supports infinite length generation using a novel Parallel Denoising scheme. 2. checkpoint available for virtual human video generation trained on human dataset. 3. supports Image2Video, Text2Image2Video, Video2Video. 4. compatible with the Stable Diffusion ecosystem, including `base_model`, `lora`, `controlnet`, etc. 5. supports multi reference image technology, including `IPAdapter`, `ReferenceOnly`, `ReferenceNet`, `IPAdapterFaceID`. 6. training codes (comming very soon). ## Model ### overview of model structure ![model_structure](data/models/musev_structure.png) ### parallel denoise ![parallel_denoise](data/models/parallel_denoise.png) ## Cases All frames are generated from text2video model, without any post process. Bellow Case could be found in `configs/tasks/example.yaml` ### Text/Image2Video #### Human )
image video prompt
(masterpiece, best quality, highres:1),(1girl, solo:1),(beautiful face, soft skin, costume:1),(eye blinks:{eye_blinks_factor}),(head wave:1.3)
(masterpiece, best quality, highres:1),(1girl, solo:1),(beautiful face, soft skin, costume:1),(eye blinks:{eye_blinks_factor}),(head wave:1.3)
(masterpiece, best quality, highres:1), peaceful beautiful sea scene
(masterpiece, best quality, highres:1), peaceful beautiful sea scene
(masterpiece, best quality, highres:1), peaceful beautiful sea scene
(masterpiece, best quality, highres:1), playing guitar
(masterpiece, best quality, highres:1), playing guitar
(masterpiece, best quality, highres:1), playing guitar
(masterpiece, best quality, highres:1), playing guitar
(masterpiece, best quality, highres:1),(1man, solo:1),(beautiful face, soft skin, costume:1),(eye blinks:{eye_blinks_factor}),(head wave:1.3)
(masterpiece, best quality, highres:1),(1girl, solo:1),(beautiful face, soft skin, costume:1),(eye blinks:{eye_blinks_factor}),(head wave:1.3)
(masterpiece, best quality, highres:1),(1man, solo:1),(beautiful face, soft skin, costume:1),(eye blinks:{eye_blinks_factor}),(head wave:1.3)
(masterpiece, best quality, highres:1),(1girl, solo:1),(beautiful face, soft skin, costume:1),(eye blinks:{eye_blinks_factor}),(head wave:1.3)
(masterpiece, best quality, highres:1),(1girl, solo:1),(beautiful face, soft skin, costume:1),(eye blinks:{eye_blinks_factor}),(head wave:1.3)
#### scene
image video prompt
(masterpiece, best quality, highres:1), peaceful beautiful waterfall, an endless waterfall
(masterpiece, best quality, highres:1), peaceful beautiful river
(masterpiece, best quality, highres:1), peaceful beautiful sea scene
### VideoMiddle2Video # News - [03/22/2024] release `MuseV` project and trained model `musev`, `muse_referencenet`. # Quickstart please refer to [MuseV](https://github.com/TMElyralab/MuseV) ### Gradio demo MuseV provides gradio script to generate GUI in local machine to generate video conveniently. ```bash cd scripts/gradio python app.py ``` # Acknowledgements MuseV builds on `TuneAVideo`, `diffusers`. Thanks for open-sourcing! # Citation **paper comming soon** ```bib @article{musev, title={MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Parallel Denoising}, author={Xia, Zhiqiang and Chen, Zhaokang and Wu, Bin and Li, Chao and Hung, Kwok-Wai and Zhan, Chao and Zhou, Wenjiang}, journal={arxiv}, year={2024} } ``` # Disclaimer/License 1. `code`: The code of MuseV is released under the MIT License. There is no limitation for both academic and commercial usage. 1. `model`: The trained model are available for non-commercial research purposes only. 1. `other opensource model`: Other open-source models used must comply with their license, such as `insightface`, `IP-Adapter`, `ft-mse-vae`, etc. 1. `AIGC`: This project strives to impact the domain of AI-driven video generation positively. Users are granted the freedom to create videos using this tool, but they are expected to comply with local laws and utilize it responsibly. The developers do not assume any responsibility for potential misuse by users.