Awesome
EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer
Official PyTorch implementation of ECCV 2022 paper "EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer"
Chenyu Yang, Wanrong He, Yingqing Xu, and Yang Gao.
Getting Started
Test
To test our model, download the weights of the trained model and run
python scripts/demo.py
Examples of makeup transfer results can be seen here.
Train
To train a model from scratch, run
python scripts/train.py
Customized Transfer
This is our demo of customized makeup editing. The interactive system is built upon Streamlit and the interface in ./training/inference.py
.
Controllable makeup transfer.
Local makeup editing.
Citation
If this work is helpful for your research, please consider citing the following BibTeX entry.
@article{yang2022elegant,
title={EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer},
author={Yang, Chenyu and He, Wanrong and Xu, Yingqing and Gao, Yang}
journal={arXiv preprint arXiv:2207.09840},
year={2022}
}
Acknowledgement
Some of the codes are build upon PSGAN and aster.Pytorch.
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.