Illusion3D generates 3D objects with multicolor textures that reveal different pictures from different viewpoints, using a 2D text-to-image diffusion model and score-distillation optimization.
Evolving Three Dimension (3D) Abstract Art: Fitting Concepts by Language
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abstract
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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Illusion3D: 3D Multiview Illusion with 2D Diffusion Priors
Illusion3D generates 3D objects with multicolor textures that reveal different pictures from different viewpoints, using a 2D text-to-image diffusion model and score-distillation optimization.