CVLGApr 24, 2023

Evolving Three Dimension (3D) Abstract Art: Fitting Concepts by Language

arXiv:2304.12932v11 citationsh-index: 17
Originality Incremental advance
AI Analysis

This addresses a gap in computational creativity for artists seeking to express abstract 3D ideas with controllability, though it appears incremental as it extends existing methods to a new domain.

The paper tackles the problem of creating high-quality, controllable abstract 3D art by bridging evolution strategies and 3D rendering, demonstrating that it can place semi-transparent triangles to render films matching artists' language specifications.

Computational creativity has contributed heavily to abstract art in modern era, allowing artists to create high quality, abstract two dimension (2D) arts with a high level of controllability and expressibility. However, even with computational approaches that have promising result in making concrete 3D art, computationally addressing abstract 3D art with high-quality and controllability remains an open question. To fill this gap, we propose to explore computational creativity in making abstract 3D art by bridging evolution strategies (ES) and 3D rendering through customizable parameterization of scenes. We demonstrate that our approach is capable of placing semi-transparent triangles in 3D scenes that, when viewed from specified angles, render into films that look like artists' specification expressed in natural language. This provides a new way for the artist to easily express creativity ideas for abstract 3D art. The supplementary material, which contains code, animation for all figures, and more examples, is here: https://es3dart.github.io/

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