Deep Convolutional Neural Networks (DCNNs) have made surprising progress in synthesising high-quality and coherent images. The best performing neural network architectures in the generative domain are the class of Generative Adversarial Networks (GANs). These networks have been applied in many different scenarios: domain transfer of images, e.g. going from sunny to winter environments; generating images from text descriptions; using computer generated data to train neural networks for real world settings; and many other domains.