Exploring Bridges Between Algorithmic and AI-generated Art

TL;DR

This paper introduces two systems that integrate AI and algorithmic art, enabling style transfer and AI feature application to enhance creative coding and artistic expression.

Contribution

It presents novel tools that connect AI and algorithmic art, allowing style transfer and AI feature integration within creative coding environments.

Findings

GenP5 enables diffusion-based style transfer in p5.js

P52Style learns and applies styles from algorithmic artifacts

The systems demonstrate enhanced artistic possibilities

Abstract

In this paper, we bridge algorithmic and AI art by adding functionality to the creative coding environment. We create two systems that demonstrate how AI features can enhance algorithmic art and, conversely, how AI art can be styled based on algorithmically-generated artifacts. The first library, GenP5, extends p5.js to allow the artist to apply diffusion models to style and 'condition' their algorithmically-constructed art. The second, P52Style, can learn the 'style' of an algorithmically generated artifact and apply that when creating new AI art.