A Hypothesis for the Aesthetic Appreciation in Neural Networks

• URL: http://arxiv.org/abs/2108.02646v1
• Date: Sat, 31 Jul 2021 06:19:00 GMT
• Title: A Hypothesis for the Aesthetic Appreciation in Neural Networks
• Authors: Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Quanshi Zhang
• Abstract summary: This paper proposes a hypothesis for the aesthetic appreciation that aesthetic images make a neural network strengthen salient concepts and discard inessential concepts. In experiments, we find that the revised images are more aesthetic than the original ones to some extent.
• Score: 17.58003267114874
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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