Code for reproducing most of the results in the paper. Triple-GAN: a unified GAN model for classification and class-conditional generation in semi-supervised learning.
Warning: the code is still under development.
Envoronment settings and libs we used in our experiments
This project is tested under the following environment setting.
OS: Ubuntu 16.04.3
GPU: Geforce 1080 Ti or Titan X(Pascal or Maxwell)
Thank the authors of these libs. We also thank the authors of Improved-GAN and Temporal Ensemble for providing their code. Our code is widely adapted from their repositories.
Results
Triple-GAN can achieve excellent classification results on MNIST, SVHN and CIFAR10 datasets, see the paper for a comparison with the previous state-of-the-art. See generated images as follows: