Generative Adversarial Networks (GAN) - Introduction

CNN are well suited for image classification • But is it possible to exploit them to create an image generator? • GANs are implemented as a min-max two-player game between two systems: a Generator G and a Discriminator D • In adversarial training, the goal of the generator is to create images are seem as real as possible. The goal of the discriminator it to detect which images are real and which are generated • They are trained in cycles. At the end, the discriminator can be thrown away and we have a generator that can create seemingly real images from random noise.