Co-training Generative Adversarial Networks

This research project focuses on improving the performance of Generative Adversarial Networks (GAN) using the features from co-training techniques. In order to mitigate the ‘mode collapse’ problem, this research aims to use multiple generators and discriminators to train the network, such that each generator or discriminator is able to learn one view from the whole training data space.