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Non-Commercial use only!

This is the current best-in-class virtual try-on model, created by the Korea Advanced Institute of Science & Technology (KAIST). It’s capable of virtual try-on “in the wild” which has notoriously been difficult for generative models to tackle, until now!

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 - project page

teaser teaser2

TODO LIST

[x] demo model
[x] inference code
[ ] training code

Acknowledgements

For the demo, auto masking generation codes are based on OOTDiffusion and DCI-VTON.
Parts of the code are based on 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.

cuuupid / idm-vton

Input

Output

Examples

Run time and cost