PyTorch implementation for paper Neural Marching Cubes
NMC
PyTorch implementation for paper Neural Marching Cubes, Zhiqin Chen, Hao Zhang.
Citation
If you find our work useful in your research, please consider citing:
@article{chen2021nmc,
title={Neural Marching Cubes},
author={Zhiqin Chen and Hao Zhang},
journal={arXiv preprint arXiv:2106.11272},
year={2021}
}
Notice
We have implemented Neural Dual Contouring (NDC).
NDC is based on Dual Contouring and thus much easier to implement than NMC.
It produces less triangles and vertices (1/8 of NMC, 1/4 of NMC-lite, ≈MC33), with better triangle quality.
It runs faster than NMC because it has significantly less values to predict for each cube (1 bool 3 float for NDC, v.s. 5 bool 51 float for NMC), therefore the network size could be significantly reduced.
Yet, it cannot reconstruct some cube cases, and may introduce non-manifold edges.
Requirements