Coupled Generative Adversarial Network code
This is the open source repository for the Coupled Generative Adversarial Network (CoupledGAN or CoGAN) work. For more details please refer to our NIPS 2016 paper or our arXiv paper. Please cite the NIPS paper in your publications if you find the source code useful to your research.
I have improved the algorithm by combining with encoders. For more details please check our NIPS 2017 paper on Unsupervised Image-to-Image Translation Networks
In this repository, we provide both Caffe implementation and PyTorch implementation. For using the code with the Caffe library, please consult USAGE_CAFFE. For using the code with the PyTorch library, please consult USAGE_PYTORCH.
CoGAN Network Architecture
CoGAN learn to generate corresponding smile and non-smile faces
CoGAN learn to generate corresponding faces with blond-hair and without non-blond-hair
CoGAN learn to generate corresponding faces with eye-glasses and without eye-glasses
CoGAN learn to generate corresponding RGB and depth images
Copyright 2017, Ming-Yu Liu All Rights Reserved
Permission to use, copy, modify, and distribute this software and its documentation for any non-commercial purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation, and that the name of the author not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission.
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