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arXiv · 2108.02646

A Hypothesis for the Aesthetic Appreciation in Neural Networks

Xu Cheng·Xin Wang·Haotian Xue·Zhengyang Liang·Quanshi Zhang
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Abstract

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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Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Quanshi Zhang. 2021-07-31. A Hypothesis for the Aesthetic Appreciation in Neural Networks. https://arxiv.org/abs/2108.02646

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