CA-GAN: Composition-Aided GANs, IEEE TCYB, 2020
We provide PyTorch implementation for CA-GAN and SCA-GAN.
Paper "Towards Realistic Face Photo-Sketch Synthesis via Composition-Aided GANs"
[Paper@IEEE] [Project@Github] [Paper@arxiv] [Project Page]
left: sketch synthesis; right: photo synthesis
(a)Input Image, (b)cGAN, (c)CA-GAN, (d)SCA-GAN
Clone this repo:
git clone https://github.com/fei-hdu/ca-gan
cd ca-gan
Install PyTorch 0.4+ and torchvision from http://pytorch.org and other dependencies (e.g., visdom and dominate). You can install all the dependencies by
pip install -r requirments.txt
python main.py --model_vgg {model path}
python test.py --dataroot {data path} --fold {epoch number}
fold
is used for load ./checkpoint/netG_epoch_'+fold+'.weight
and you can edit it in test.py
./checkpoint
and named it as netG_epoch_'+fold+'.weight
Best practice for training and testing your models. Feel free to ask any questions about coding. Xingxin Xu, [email protected]
If you find this useful for your research, please cite our paper as:
@article{gao2020ca-gan,
title = {Towards Realistic Face Photo-Sketch Synthesis via Composition-Aided GANs},
author = {Jun Yu and Xingxin Xu and Fei Gao and Shengjie Shi and Meng Wang and Dacheng Tao and and Qingming Huang},
booktitle = {IEEE Transactions on Cybernatics},
doi = {10.1109/TCYB.2020.2972944},
year = {2020},
url = {https://github.com/fei-hdu/ca-gan},
}