A Unified Differentiable Boolean Operator with Fuzzy Logic

Public code release for "A Unified Differentiable Boolean Operator with Fuzzy Logic". For more details, please refer to:

Surface Simplification using Intrinsic Error Metrics
Hsueh-Ti Derek Liu, Maneesh Agrawala, Cem Yuksel, Tim Omernick, Vinith Misra, Stefano Corazza, Morgan McGuire, Victor Zordan
SIGGRAPH 2024
[Preprint] [ArXiv]

Installation

To get started, clone this repository

git clone https://github.com/HTDerekLiu/fuzzy-boolean.git

This code depends on libigl, PyMCubes, PyTorch and some common python dependencies (e.g., NumPy).

Layout

Each folder contains stand-alone examples that demonstrate some core functionalities of our proposed technique. All of them have a similar directory and file layout:

• 00_product_fuzzy_boolean/: a minimal example to demonstrate how to perform boolean operations with the Product Fuzzy Logic.
• 01_inverse_csg_2D/: performs inverse CSG optimization on a simple 2D example with an output CSG tree.
• 02_inverse_csg_quadrics_3D/: shows inverse CSG optimization on a single 3D shape.

And they share a common utils folder for basic functionalities.

Execution

Running the code is very simple, one can simply do

cd 00_product_fuzzy_boolean
python main.py

Citation

If this code contributes to academic work, please cite as:

@inproceedings{Liu:2024:FuzzyBoolean,
    author = {Liu, Hsueh-Ti Derek and Agrawala, Maneesh and Yuksel, Cem and Omernick, Tim and Misra, Vinith and Corazza, Stefano and Mcguire, Morgan and Zordan, Victor},
    title = {A Unified Differentiable Boolean Operator with Fuzzy Logic},
    year = {2024},
    isbn = {9798400705250},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3641519.3657484},
    doi = {10.1145/3641519.3657484},
    booktitle = {ACM SIGGRAPH 2024 Conference Papers},
    articleno = {109},
    location = {Denver, CO, USA},
    series = {SIGGRAPH '24}
}