[1706.07068] CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms
Pedro Pinto

Abstract: We propose a new system for generating art. The system generates art by looking at art and learning about style; and becomes creative by increasing the arousal potential of the generated art by deviating from the learned styles. We build over Generative Adversarial Networks (GAN), which have shown the ability to learn to generate novel images simulating a given distribution.