29.4 GB
30 files
Updated 14 days ago
Name
Size
assets
densepose
humanparsing
image_encoder
openpose
scheduler
text_encoder
text_encoder_2
tokenizer
tokenizer_2
unet
unet_encoder
vae
.gitattributes1.63 kB
xet
README.md1.56 kB
xet
model_index.json750 Bytes
xet
README.md

Check out more codes on our github repository!

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'

🤗 Try our huggingface Demo

teaser  teaser2 

TODO LIST

  • demo model
  • inference code
  • training code

Acknowledgements

For the demo, GPUs are supported from zerogpu, and 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.

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29.4 GB
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30
Last updated
Jun 18
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