GANs have become very popular in the last few years. Every week there are some advancements being made in the area of GANs. It has become one of the important subfields of deep learning, with a very active research community. GAN was introduced by Ian Goodfellow in 2014. The GAN addresses the problem of unsupervised learning by training two deep neural networks, called generator and discriminator, which compete with each other. In the course of training, both eventually become better at the tasks that they perform.
GANs are intuitively understood using the case of counterfeiter (generator) and the police (discriminator). Initially, the counterfeiter shows the police fake money. The police identifies it as fake and explains to the counterfeiter why it is fake. The counterfeiter makes new fake money based on the feedback it received. The police finds...
