The idea behind GANs is much more understandable when compared to other similar models. In essence, we use several neural networks to play a rather elaborate game. Just like in the movie Catch-me-if-you-can. For those who are not familiar with the plot of this film, we apologize in advance for any missed allusions.
We can think of a GAN as a system of two actors. On one side, we have a Di Caprio-like network that attempts to recreate some Monets and Dalis and ship them off to unsuspecting art dealers. We also have a vigilant Tom Hanks-style network that intercepts these shipments and identifies any forgeries present. As time goes by, both individuals become better at what they do, leading to realistic forgeries on the conman's side, and a keen eye for them on the cop's side. This variation of a commonly used analogy indeed does well at introducing the...
