A Hypothesis for the Aesthetic Appreciation in Neural Networks

Understand

This paper proposes a hypothesis for the aesthetic appreciation that aesthetic images make a neural network strengthen salient concepts and discard inessential concepts.

• In order to verify this hypothesis, we use multi-variate interactions to represent salient concepts and inessential concepts contained in images.
• Furthermore, we design a set of operations to revise images towards more beautiful ones.
• In experiments, we find that the revised images are more aesthetic than the original ones to some extent.