# Aesthetics of Neural Network Art

arXiv: https://arxiv.org/abs/1903.05696 · HTML: https://mlsanity.com/paper/1903.05696/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Mar 2019.

## Built on by (most cited first, 3 of 3)

- [Optimizing Latent Space Directions For GAN-based Local Image Editing](https://mlsanity.com/paper/2111.12583/) (2021)
- [Assessing aesthetics of generated abstract images using correlation structure](https://mlsanity.com/paper/2105.08635/) (2021)
- [Aesthetics and neural network image representations](https://mlsanity.com/paper/2109.08103/) (2021)

## Abstract (arXiv)

This paper proposes a way to understand neural network artworks as juxtapositions of natural image cues. It is hypothesized that images with unusual combinations of realistic visual cues are interesting, and, neural models trained to model natural images are well-suited to creating interesting images. Art using neural models produces new images similar to those of natural images, but with weird and intriguing variations. This analysis is applied to neural art based on Generative Adversarial Networks, image stylization, Deep Dreams, and Perception Engines.