Awesome

Awesome Virtual Tryon

Visual Comparison

We provide visualization results of various state-of-the-art methods to facilitate your experimental comparisons.

Visualization results of CP-VTON, CP-VTON+, ClothFlow, ACGPN, PF-AFN, DCTON, RT-VTON and our DOC-VTON.

Auxiliary test data

We provide densepose results of VITON test imgs.

We reprocess the densepose results and human parsing results of VITON-HD (Training and Testing dataset). You can download them through Baiduyun. PWD: deh8.

Tips for Coding

We recommend using PF-AFN as codebase, which contains tensorboard, DDP training set, and nice code.

DOC-VTON

Official Codes for OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided Mixup (TMM 2023)

Our Environment

anaconda3

pytorch 1.1.0

torchvision 0.3.0

cuda 9.0

cupy 6.0.0

opencv-python 4.5.1

python 3.6

Installation

conda create -n tryon python=3.6

source activate tryon or conda activate tryon

conda install pytorch=1.1.0 torchvision=0.3.0 cudatoolkit=9.0 -c pytorch

conda install cupy or pip install cupy==6.0.0

pip install opencv-python

Test Script

python test_w_enhance.py --name demo --resize_or_crop None --batchSize 1 --gpu_ids=1

Checkpoints Downlowd Address

Checkpoints for Test

License

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

Citation

Please cite if our work is useful for your research:

@article{2023occlumix,
  title={OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided Mixup},
  author={Yang, Zhijing and Chen, Junyang and Shi, Yukai and Li, Hao and Chen, Tianshui and Lin, Liang},
  journal={arXiv preprint arXiv:2301.00965},
  year={2023}
}

@article{2023occlumix,
  author={Yang, Zhijing and Chen, Junyang and Shi, Yukai and Li, Hao and Chen, Tianshui and Lin, Liang},
  journal={IEEE Transactions on Multimedia}, 
  title={OccluMix: Towards De-Occlusion Virtual Try-On by Semantically-Guided Mixup}, 
  year={2023},
  volume={},
  number={},
  pages={1-12},
  doi={10.1109/TMM.2023.3234399}}