Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation

Project | Paper

This repository contains our Tensorflow implementation for "Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation".

Prerequisites

• Linux 16.04+
• Python 3.5+
• NVIDIA GPU + CUDA CuDNN

Getting Started

Data

Download dataset from CycleGAN dataset and data in input folder.

Or you can do (e.g. summer2winter_yosemite)

bash ./input/download_cyclegan_dataset.sh summer2winter_yosemite

Train/Test

• Train a model (e.g. summer2winter_yosemite) by

python train.py --dataroot input --category summer2winter_yosemite --outroot output

• Visualize training progress

tensorboard --logdir output/summer2winter_yosemite/log

Citation

If you this code for your research, please cite our paper.

@article{xie2021cyclecoopnets,
    title={Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation},
    author={Xie, Jianwen and Zheng, Zilong and Fang, Xiaolin and Zhu, Song-Chun and Wu, Ying Nian},
    journal={The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI)},
    year={2021}
}

Acknowledgements

This code is inspired by pytorch-CycleGAN-and-pix2pix