Conditional Generative Adversarial Nets

Conditional Generative Adversarial Nets — Turn Labels Into Pictures

This idea pairs two simple computer programs that learn by competing.
One tries to create images, the other tries to tell if an image is real or made.
By giving both programs the same hint — like a class name — they learn to make things that match that hint.
With a conditional hint the generator can draw digits or scenes that fit what you asked for, and the discriminator helps keep the results honest.
People used this to make clear examples of handwritten numbers, like MNIST digits, but it can do more than numbers.
It can suggest useful image tags and sometimes invent descriptive words that weren't in the training list, surprising you.
The process is simple to try yet often produces rich, varied pictures.
It feels like telling a digital artist what to paint and watching it learn, little by little, to match your words even when you dont give perfect instructions.

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Conditional Generative Adversarial Nets

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