CCoopNets

This repo contains Tensorflow implementation for the paper:

Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning
In TPAMI 2021

Paper | Project

Getting Started

Install

• Dependencies:

  • Python3
  • Tensorflow1.4+

• Clone this repo:

git clone https://github.com/zilongzheng/CCoopNets.git

• Install python requirements:

pip install -r requirements.txt

Datasets

We use datasets from the following resources. Download before you are using any of these.

• cityscapes
• CMP Facade
  • You can create dataset by

  bash ./scripts/prepro/make_facades_dataset.sh [base|extended]

• CUHK Face
• UT-Zap50K
  • The preprocessing code is here.

Note: We use dataroot/category/<original datapath> for most of the datasets, change relative path declared here based on your path organization.

Exp1: Category to Image

• Train mnist data

sh scripts/train_cat2img_mnist.sh --dataroot datasets --output_dir output

Exp2: Image to Image

• Train facade2photo

sh scripts/train_img2img_facade2photo.sh --dataroot datasets --output_dir output

Logs

The output is recorded using tensorboard, which can be visualized by

tensorboard --logdir output/<category>_<timestamp>/log/

Citation

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

@article{xie2021ccoopnets,
  author={Xie, Jianwen and Zheng, Zilong and Fang, Xiaolin and Zhu, Song-Chun and Wu, Ying Nian},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning}, 
  year={2021},
  doi={10.1109/TPAMI.2021.3069023}}