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By requesting access, you agree NOT to use this dataset or its content for any commercial purposes, and NOT to redistribute any part of it publicly or privately.
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---
Okay, I can help with that. Here is the updated README with the provided links, formatted to be left-aligned.
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# DressCode-MR: A Large-Scale Multi-Reference Virtual Try-On Dataset
Supported by [LavieAI](https://lavieai.com/) and [LoomlyAI](https://www.loomlyai.com/en)
[arXiv](https://arxiv.org/abs/2508.20586) | [Hugging Face](https://huggingface.co/zhengchong/FastFit-MR-1024) | [GitHub](https://github.com/Zheng-Chong/FastFit) | [Demo](https://fastfit.lavieai.com) | [License](https://github.com/Zheng-Chong/FastFit/tree/main)
**DressCode-MR** is a large-scale, multi-reference virtual try-on dataset constructed upon the original [DressCode](https://github.com/aimagelab/dress-code) dataset. It contains over **28,000 multi-reference virtual try-on samples** designed to facilitate and evaluate virtual try-on models capable of handling multiple fashion items—such as tops, bottoms, dresses, shoes, and bags—simultaneously.
## Dataset Details
* **Multi-Reference Samples**: Each sample consists of a person's image paired with a set of compatible clothing and accessory items, enabling models to learn how to coordinate multiple fashion pieces within a single scene.
* **Large Scale**: The dataset includes a total of **28,179** high-quality multi-reference samples, with **25,779** designated for training and **2,400** for testing.
* **Source**: This dataset is built upon the [DressCode](https://github.com/aimagelab/dress-code) dataset.
## Access and License
This dataset is released under the exact same license as the original [DressCode](https://github.com/aimagelab/dress-code) dataset. Therefore, before you can request access to the **DressCode-MR** dataset, you must first complete the following steps:
1. Apply for and be granted a license to use the [DressCode](https://github.com/aimagelab/dress-code) dataset.
2. Use your educational/academic email address (e.g., one ending in `.edu`, `.ac`, etc.) to request access to the **DressCode-MR** dataset on Hugging Face. **Any requests from non-academic email addresses will be rejected.**
## Usage
After downloading the dataset, you can decompress the files using the following commands:
```bash
cat DressCode-MR.tar.gz.part_* > DressCode-MR.tar.gz
tar -zxvf DressCode-MR.tar.gz
```
## Citation
If you use the **DressCode-MR** dataset in your research, please cite our [FastFit](https://arxiv.org/abs/2508.20586) paper.
```bibtex
@misc{chong2025fastfitacceleratingmultireferencevirtual,
title={FastFit: Accelerating Multi-Reference Virtual Try-On via Cacheable Diffusion Models},
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},
year={2025},
eprint={2508.20586},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2508.20586},
}
```
## Acknowledgement
We thank the contributors to the [DressCode](https://github.com/aimagelab/dress-code) project, as their work provided the foundation for our **DressCode-MR** dataset.