This is an implementation of the Coupled Generative Adversarial Netowork algorithm. For more details please refer to our NIPS paper.

Please cite the CoGAN paper in your publications if it is the code is useful to your research.

Also, a PyTorch implementation of CoGAN is available in https://github.com/mingyuliutw/CoGAN_PyTorch.

caffe/

The folder contains a modified version of Caffe. It includes a new solver and several new layers for supporting back propagation with alternating gradient update steps. Note that several existing classes were modified for the same need.

cogan/

The folder contains the solver and network definition files.

build.sh

A script for building the Caffe library.

train_cogan.sh

A script for train a CoGAN net.

test_cogan.sh

A script for visualizing CoGAN training results.

./build.sh ./train_cogan.sh ./test_cogan.sh

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