# Topology Optimization with Text-Guided Stylization

arXiv: https://arxiv.org/abs/2310.15506 · HTML: https://mlsanity.com/paper/2310.15506/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Oct 2023.

## Built on by (most cited first, 4 of 4)

- [Zero-shot rib design: merging training-free generative prior with topology optimization](https://mlsanity.com/paper/2609.10643/) (2026)
- [Generating Physically Sound Designs from Text and a Set of Physical Constraints](https://mlsanity.com/paper/2602.02213/) (2026)
- [Planar Symmetric Pattern Generation](https://mlsanity.com/paper/2606.02073/) (2026)
- [How the Classical Baseline Shapes Machine-Learning Speed Claims in Topology Optimization](https://mlsanity.com/paper/2610.16051/) (2026)

## Abstract (arXiv)

We propose an approach for the generation of topology-optimized structures with text-guided appearance stylization. This methodology aims to enrich the concurrent design of a structure's physical functionality and aesthetic appearance. Users can effortlessly input descriptive text to govern the style of the structure. Our system employs a hash-encoded neural network as the implicit structure representation backbone, which serves as the foundation for the co-optimization of structural mechanical performance, style, and connectivity, to ensure full-color, high-quality 3D-printable solutions. We substantiate the effectiveness of our system through extensive comparisons, demonstrations, and a 3D printing test.