Lidan Wang, Vishwanath Singagi, Vishal M. Patel
If you use this code for your research, please cite our paper
@inproceedings{wang2018high,
title={High-quality facial photo-sketch synthesis using multi-adversarial networks},
author={Wang, Lidan and Sindagi, Vishwanath and Patel, Vishal},
booktitle={Automatic Face \& Gesture Recognition (FG 2018), 2018 13th IEEE International Conference on},
pages={83--90},
year={2018},
organization={IEEE}
}
- Linux
- Python 2 or Python 3
- NVIDIA GPU + CUDA CuDNN
- Install PyTorch and dependencies from http://pytorch.org/
- Install Torch vision from the source.
- Install python libraries visdom.
pip install visdom
make sure the data folder has subfolders trainA, trainB, valA, valB, testA, testB
python PS2MAN.py --dataroot 'data/cuhkdata_augmented' --ckpt_path 'ckpt'
CycleGAN: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
pix2pix: Image-to-image translation with conditional adversarial nets
DualGAN: DualGAN: Unsupervised Dual Learning for Image-to-Image Translation
This code is modified based on:
CycleGAN: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
We thank the authors for their great work.