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@@ -33,5 +33,18 @@ We further demonstrate the superiority of I2I priors over T2I priors on some tex
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  ## 🚀 Model Structure
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  ![pipeline](asset/method.png)
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  ## 🚀 Model Structure
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  ![pipeline](asset/method.png)
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+ [Lumos](https://arxiv.org/pdf/2412.07767) consists of transformer blocks for latent diffusion, which is applied for various visual generative tasks such as text-to-image, image-to-3D, and image-to-video generation.
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+ Source code is available at https://github.com/xiaomabufei/lumos.
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+ ### Model Description
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+ - **Developed by:** Lumos-I2I
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+ - **Model type:** Diffusion-Transformer-based generative model
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+ - **License:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md)
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+ - **Model Description:** This is a model that can be used to generate and modify images based on image prompt.
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+ It is a [Transformer Latent Diffusion Model](https://arxiv.org/abs/2310.00426) that uses one fixed, pretrained vision encoders ([DINO](
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+ https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_pretrain.pth))
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+ and one latent feature encoder ([VAE](https://arxiv.org/abs/2112.10752)).
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+ - **Resources for more information:** Check out our [GitHub Repository](https://github.com/xiaomabufei/lumos) and the [Lumos report on arXiv](https://arxiv.org/pdf/2412.07767).
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