Searching for “mountain” in your Apple/Google photos library, browsing the Related Pins section in Pinterest, or using Google Lens to find information about the world around you - these are all instances of content-based search. With the increasing ubiquity of cameras, more and more of the data we create is visual: 400 hours worth of videos are uploaded to Youtube every minute, 80 million photos are shared on Instagram on an average day.
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.