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@@ -23,14 +23,15 @@ metrics:
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  - lpips
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  base_model: "runwayml/stable-diffusion-inpainting"
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  ---
 
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  <h1 align="center"> FastFit: Accelerating Multi-Reference Virtual Try-On via Cacheable Diffusion Models </h1>
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  <p align="center" style="font-size: 18px;">Supported by <a href="https://lavieai.com/">LavieAI</a> and <a href="https://www.loomlyai.com/en">LoomlyAI</a></p>
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  <div align="center">
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- <a href="https://github.com/Zheng-Chong/FastFit" style="margin: 0 2px; text-decoration: none;">
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- <img src='https://img.shields.io/badge/arXiv-TODO-red?style=flat&logo=arXiv&logoColor=red' alt='arxiv'>
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  </a>
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  <a href='https://huggingface.co/zhengchong/FastFit-MR-1024' style="margin: 0 2px; text-decoration: none;">
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  <img src='https://img.shields.io/badge/Hugging Face-ckpts-orange?style=flat&logo=HuggingFace&logoColor=orange' alt='huggingface'>
@@ -41,9 +42,6 @@ base_model: "runwayml/stable-diffusion-inpainting"
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  <a href="https://fastfit.lavieai.com" style="margin: 0 2px; text-decoration: none;">
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  <img src='https://img.shields.io/badge/Demo-Gradio-gold?style=flat&logo=Gradio&logoColor=red' alt='Demo'>
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  </a>
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- <a href='https://zheng-chong.github.io/FastFit/' style="margin: 0 2px;">
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- <img src='https://img.shields.io/badge/Webpage-Project-silver?style=flat&logo=&logoColor=orange' alt='webpage'>
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- </a>
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  <a href="https://github.com/Zheng-Chong/FastFit/tree/main" style="margin: 0 2px; text-decoration: none;">
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  <img src='https://img.shields.io/badge/License-NonCommercial-lightgreen?style=flat&logo=Lisence' alt='License'>
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  </a>
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  FastFit is a diffusion-based framework optimized for **high-speed**, **multi-reference virtual try-on**. It enables **simultaneous try-on of multiple fashion items**—such as **tops, bottoms, dresses, shoes, and bags**—on a single person. The framework leverages **reference KV caching** during inference to **significantly accelerate generation**.
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  ## Updates
 
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  - **`2025/08/06`**: ⚙️ We release [the code for inference and evaluation](https://github.com/Zheng-Chong/FastFit/tree/main?tab=readme-ov-file#inference--evaluation-on-datasets) on the [DressCode-MR](https://huggingface.co/datasets/zhengchong/DressCode-MR), [DressCode](https://huggingface.co/datasets/zhengchong/DressCode-Test), and [VITON-HD](https://huggingface.co/datasets/zhengchong/VITON-HD) test datasets.
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  - **`2025/08/05`**: 🧩 We release the [ComfyUI workflow](https://github.com/Zheng-Chong/FastFit/releases/tag/comfyui) for FastFit!
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  - **`2025/08/04`**: 🚀 Our [gradio demo](https://fastfit.lavieai.com) is online with Chinese & English support! The code of the demo is also released in [app.py](app.py).
@@ -174,15 +173,23 @@ python eval.py \
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  - `--paired`: Include this flag to evaluate results from the paired setting. Omit this flag for the unpaired setting.
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- <!-- ## Citation
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  ```bibtex
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-
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- ``` -->
 
 
 
 
 
 
 
 
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  ## Acknowledgement
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  Our code is modified based on [Diffusers](https://github.com/huggingface/diffusers). We adopt [Stable Diffusion v1.5 inpainting](https://huggingface.co/runwayml/stable-diffusion-inpainting) as the base model. We use a modified [AutoMasker](https://github.com/Zheng-Chong/CatVTON/blob/edited/model/cloth_masker.py) to automatically generate masks in our [Gradio](https://github.com/gradio-app/gradio) App and [ComfyUI](https://github.com/comfyanonymous/ComfyUI) workflow. Thanks to all the contributors!
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  ## License
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- All weights, parameters, and code related to FastFit are governed by the [FastFit Non-Commercial License](https://github.com/Zheng-Chong/FastFit/tree/main). For commercial collaboration, please contact [LavieAI](https://lavieai.com/) or [LoomlyAI](https://www.loomlyai.com/en).
 
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  - lpips
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  base_model: "runwayml/stable-diffusion-inpainting"
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  ---
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+
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  <h1 align="center"> FastFit: Accelerating Multi-Reference Virtual Try-On via Cacheable Diffusion Models </h1>
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  <p align="center" style="font-size: 18px;">Supported by <a href="https://lavieai.com/">LavieAI</a> and <a href="https://www.loomlyai.com/en">LoomlyAI</a></p>
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  <div align="center">
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+ <a href="https://arxiv.org/abs/2508.20586" style="margin: 0 2px; text-decoration: none;">
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+ <img src='https://img.shields.io/badge/arXiv-2508.20586-red?style=flat&logo=arXiv&logoColor=red' alt='arxiv'>
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  </a>
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  <a href='https://huggingface.co/zhengchong/FastFit-MR-1024' style="margin: 0 2px; text-decoration: none;">
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  <img src='https://img.shields.io/badge/Hugging Face-ckpts-orange?style=flat&logo=HuggingFace&logoColor=orange' alt='huggingface'>
 
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  <a href="https://fastfit.lavieai.com" style="margin: 0 2px; text-decoration: none;">
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  <img src='https://img.shields.io/badge/Demo-Gradio-gold?style=flat&logo=Gradio&logoColor=red' alt='Demo'>
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  </a>
 
 
 
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  <a href="https://github.com/Zheng-Chong/FastFit/tree/main" style="margin: 0 2px; text-decoration: none;">
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  <img src='https://img.shields.io/badge/License-NonCommercial-lightgreen?style=flat&logo=Lisence' alt='License'>
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  </a>
 
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  FastFit is a diffusion-based framework optimized for **high-speed**, **multi-reference virtual try-on**. It enables **simultaneous try-on of multiple fashion items**—such as **tops, bottoms, dresses, shoes, and bags**—on a single person. The framework leverages **reference KV caching** during inference to **significantly accelerate generation**.
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  ## Updates
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+ - **`2025/08/29`**: 📄 We release the [arXiv paper](https://arxiv.org/abs/2508.20586) of FastFit!
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  - **`2025/08/06`**: ⚙️ We release [the code for inference and evaluation](https://github.com/Zheng-Chong/FastFit/tree/main?tab=readme-ov-file#inference--evaluation-on-datasets) on the [DressCode-MR](https://huggingface.co/datasets/zhengchong/DressCode-MR), [DressCode](https://huggingface.co/datasets/zhengchong/DressCode-Test), and [VITON-HD](https://huggingface.co/datasets/zhengchong/VITON-HD) test datasets.
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  - **`2025/08/05`**: 🧩 We release the [ComfyUI workflow](https://github.com/Zheng-Chong/FastFit/releases/tag/comfyui) for FastFit!
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  - **`2025/08/04`**: 🚀 Our [gradio demo](https://fastfit.lavieai.com) is online with Chinese & English support! The code of the demo is also released in [app.py](app.py).
 
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  - `--paired`: Include this flag to evaluate results from the paired setting. Omit this flag for the unpaired setting.
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+ ## Citation
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  ```bibtex
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+ @misc{chong2025fastfitacceleratingmultireferencevirtual,
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+ title={FastFit: Accelerating Multi-Reference Virtual Try-On via Cacheable Diffusion Models},
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+ author={Zheng Chong and Yanwei Lei and Shiyue Zhang and Zhuandi He and Zhen Wang and Xujie Zhang and Xiao Dong and Yiling Wu and Dongmei Jiang and Xiaodan Liang},
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+ year={2025},
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+ eprint={2508.20586},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2508.20586},
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+ }
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+ ```
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  ## Acknowledgement
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  Our code is modified based on [Diffusers](https://github.com/huggingface/diffusers). We adopt [Stable Diffusion v1.5 inpainting](https://huggingface.co/runwayml/stable-diffusion-inpainting) as the base model. We use a modified [AutoMasker](https://github.com/Zheng-Chong/CatVTON/blob/edited/model/cloth_masker.py) to automatically generate masks in our [Gradio](https://github.com/gradio-app/gradio) App and [ComfyUI](https://github.com/comfyanonymous/ComfyUI) workflow. Thanks to all the contributors!
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  ## License
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+ All weights, parameters, and code related to FastFit are governed by the [FastFit Non-Commercial License](https://github.com/Zheng-Chong/FastFit/tree/main). For commercial collaboration, please contact [LavieAI](https://lavieai.com/) or [LoomlyAI](https://www.loomlyai.com/en).