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Limb-Aware Virtual Try-On Network With Progressive Clothing Warping, IEEE Transactions on Multimedia'23.

Official code for TMM 2023 paper 'Limb-Aware Virtual Try-On Network With Progressive Clothing Warping'

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We propose a novel virtual try-on network named PL-VTON, where three sub-modules are designed to generate high-quality try-on results, including Progressive Clothing Warping, Person Parsing Estimator, and Limb-aware Texture Fusion. On the one hand, PL-VTON explicitly models the location and size of the in-shop clothing and utilizes a two-stage alignment strategy to estimate the fine-grained clothing warping progressively. On the other hand, PL-VTON adopts limb-aware guidance to generate realistic limb details during the texture fusion between the warped clothing and the human body.

[Paper]

[Checkpoints]

Notice

Our method is an extension of our previous work on the conference version: https://github.com/xyhanHIT/PL-VTON, and improvements made in this article include:

  • a new pre-alignment network to regress dynamic parameters of translation and scaling
  • a novel gravity-aware loss
  • a non-limb target parsing map
  • the optimization of the clothing-agnostic person representation
  • more qualitative and quantitative experiment results

Pipeline

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Environment

python 3.8

torch 2.0.1+cu118

torchvision 0.15.2+cu118

Dataset

For the dataset, please refer to VITON.

You also need to download the data about hands from here.

Inference

  1. Download the checkpoints from here.

  2. Get VITON dataset.

  3. Run the "test.py".

python test.py

Sample Try-on Results

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License

The use of this code is restricted to non-commercial research and educational purposes.

Citation

If you use our code or models, please cite with:

@article{zhang2023limb,
  title={Limb-aware virtual try-on network with progressive clothing warping},
  author={Zhang, Shengping and Han, Xiaoyu and Zhang, Weigang and Lan, Xiangyuan and Yao, Hongxun and Huang, Qingming},
  journal={IEEE Transactions on Multimedia},
  year={2023},
  publisher={IEEE}
}
@inproceedings{han2022progressive,
  title={Progressive Limb-Aware Virtual Try-On},
  author={Han, Xiaoyu and Zhang, Shengping and Liu, Qinglin and Li, Zonglin and Wang, Chenyang},
  booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
  pages={2420--2429},
  year={2022}
}