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@@ -13,7 +13,7 @@ tags:
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- <font size=5>**MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Parallel Denoising**</font>
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  </br>
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  Zhiqiang Xia <sup>\*</sup>,
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  Zhaokang Chen<sup>\*</sup>,
@@ -345,7 +345,7 @@ MuseV builds on `TuneAVideo`, `diffusers`. Thanks for open-sourcing!
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  # Citation
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  ```bib
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  @article{musev,
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- title={MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Parallel Denoising},
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  author={Xia, Zhiqiang and Chen, Zhaokang and Wu, Bin and Li, Chao and Hung, Kwok-Wai and Zhan, Chao and Zhou, Wenjiang},
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  journal={arxiv},
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  year={2024}
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  1. `code`: The code of MuseV is released under the MIT License. There is no limitation for both academic and commercial usage.
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  1. `model`: The trained model are available for non-commercial research purposes only.
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  1. `other opensource model`: Other open-source models used must comply with their license, such as `insightface`, `IP-Adapter`, `ft-mse-vae`, etc.
 
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  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.
 
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+ <font size=5>**MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Visual Conditioned Parallel Denoising**</font>
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  </br>
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  Zhiqiang Xia <sup>\*</sup>,
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  Zhaokang Chen<sup>\*</sup>,
 
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  # Citation
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  ```bib
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  @article{musev,
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+ title={MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Visual Conditioned Parallel Denoising},
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  author={Xia, Zhiqiang and Chen, Zhaokang and Wu, Bin and Li, Chao and Hung, Kwok-Wai and Zhan, Chao and Zhou, Wenjiang},
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  journal={arxiv},
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  year={2024}
 
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  1. `code`: The code of MuseV is released under the MIT License. There is no limitation for both academic and commercial usage.
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  1. `model`: The trained model are available for non-commercial research purposes only.
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  1. `other opensource model`: Other open-source models used must comply with their license, such as `insightface`, `IP-Adapter`, `ft-mse-vae`, etc.
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+ 1. The testdata are collected from internet, which are available for non-commercial research purposes only.
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  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.