A Hypothesis for the Aesthetic Appreciation in Neural Networks

31 Jul 2021  ·  Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Quanshi Zhang ·

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.

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