Official code and instructions for the paper:
MIND: Microstructure INverse Design with Generative Hybrid Neural Representation
By Tianyang Xue, Longdu Liu, Lin Lu, Paul Henderson, Pengbin Tang, Haochen Li, Jikai Liu, Haisen Zhao, Hao Peng, Bernd Bickel
This repository provides tools for generating microstructural holoplane representations and training a diffusion model to generate physically plausible designs.
If you use this work, please cite:
@inproceedings{10.1145/3721238.3730682,
author = {Xue, Tianyang and Liu, Longdu and Lu, Lin and Henderson, Paul and Tang, Pengbin and Li, Haochen and Liu, Jikai and Zhao, Haisen and Peng, Hao and Bickel, Bernd},
title = {MIND: Microstructure INverse Design with Generative Hybrid Neural Representation},
year = {2025},
isbn = {9798400715402},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3721238.3730682},
doi = {10.1145/3721238.3730682},
booktitle = {Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers},
series = {SIGGRAPH Conference Papers '25}
}