File size: 1,558 Bytes
d66d1cc 29e2f0c d66d1cc 29e2f0c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
---
base_model: stable-diffusion-xl-1.0-inpainting-0.1
tags:
- stable-diffusion-xl
- inpainting
- virtual try-on
license: cc-by-nc-sa-4.0
---
# Check out more codes on our [github repository](https://github.com/yisol/IDM-VTON)!
# IDM-VTON : Improving Diffusion Models for Authentic Virtual Try-on in the Wild
This is an official implementation of paper 'Improving Diffusion Models for Authentic Virtual Try-on in the Wild'
- [paper](https://arxiv.org/abs/2403.05139)
- [project page](https://idm-vton.github.io/)
🤗 Try our huggingface [Demo](https://huggingface.co/spaces/yisol/IDM-VTON)
## TODO LIST
- [x] demo model
- [x] inference code
- [ ] training code
## Acknowledgements
For the demo, GPUs are supported from [zerogpu](https://huggingface.co/zero-gpu-explorers), and auto masking generation codes are based on [OOTDiffusion](https://github.com/levihsu/OOTDiffusion) and [DCI-VTON](https://github.com/bcmi/DCI-VTON-Virtual-Try-On).
Parts of the code are based on [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter).
## Citation
```
@article{choi2024improving,
title={Improving Diffusion Models for Virtual Try-on},
author={Choi, Yisol and Kwak, Sangkyung and Lee, Kyungmin and Choi, Hyungwon and Shin, Jinwoo},
journal={arXiv preprint arXiv:2403.05139},
year={2024}
}
```
## License
The codes and checkpoints in this repository are under the [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
|