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Computer Science > Machine Learning

arXiv:2108.02646 (cs)
[Submitted on 31 Jul 2021]

Title:A Hypothesis for the Aesthetic Appreciation in Neural Networks

Authors: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.
Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2108.02646 [cs.LG]
  (or arXiv:2108.02646v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2108.02646

Submission history

From: Quanshi Zhang [view email] [via Quanshi Zhang as proxy]
[v1] Sat, 31 Jul 2021 06:19:00 UTC (8,658 KB)
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