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README.md
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**[project](comming soon)** **Technical report (comming soon)**
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We have setup the world simulator vision since March 2023, believing diffusion models can simulate the world
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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!
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# Intro
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`MuseV` is a diffusion-based virtual human video generation framework, which
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1. supports infinite length generation using a novel Parallel Denoising scheme
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2. checkpoint available for virtual human video generation trained on human dataset.
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3. supports Image2Video, Text2Image2Video, Video2Video.
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4. compatible with the Stable Diffusion ecosystem
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5. supports multi reference image technology, including `IPAdapter`, `ReferenceOnly`, `ReferenceNet`, `IPAdapterFaceID`.
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6. training codes (comming very soon).
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**[project](comming soon)** **Technical report (comming soon)**
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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. Next we will move on to the promising diffusion+transformer scheme.
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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!
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# Intro
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`MuseV` is a diffusion-based virtual human video generation framework, which
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+
1. supports **infinite length** generation using a novel **Parallel Denoising scheme**.
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2. checkpoint available for virtual human video generation trained on human dataset.
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3. supports Image2Video, Text2Image2Video, Video2Video.
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4. compatible with the **Stable Diffusion ecosystem**, including `base_model`, `lora`, `controlnet`, etc.
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5. supports multi reference image technology, including `IPAdapter`, `ReferenceOnly`, `ReferenceNet`, `IPAdapterFaceID`.
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6. training codes (comming very soon).
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