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29.4 GB
30 files
Updated 14 days ago
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| Name | Size | Uploaded | Xet hash |
|---|---|---|---|
| assets | 2 items | ||
| densepose | 1 items | ||
| humanparsing | 2 items | ||
| image_encoder | 2 items | ||
| openpose | 1 items | ||
| scheduler | 1 items | ||
| text_encoder | 2 items | ||
| text_encoder_2 | 2 items | ||
| tokenizer | 4 items | ||
| tokenizer_2 | 4 items | ||
| unet | 2 items | ||
| unet_encoder | 2 items | ||
| vae | 2 items | ||
| .gitattributes | 1.63 kB xet | 766878d6 | |
| README.md | 1.56 kB xet | 5dbf9330 | |
| model_index.json | 750 Bytes xet | 6f78e16e |
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
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.
- Total size
- 29.4 GB
- Files
- 30
- Last updated
- Jun 18
- Pre-warmed CDN
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