BrepGen represents a CAD B-rep as a novel structured latent geometry hierarchical tree, with each primitive (face, edge, or vertex) progressively turns into a child-node from top to bottom. The B-rep geometry is encoded into the tree nodes along with a latent code describing the local geometric shape. The B-rep topology information is implicitly represented by node duplication.
Starting from the root and progressing to the leaf, BrepGen employs Transformer-based diffusion models to sequentially denoise node features while duplicated nodes are detected and merged, recovering the B-Rep topology information. Extensive experiments show that BrepGen advances the task of CAD B-rep generation, surpassing existing methods on various benchmarks.
@article{xu2024brepgen,
title = {BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry},
author = {Xu, Xiang and Lambourne, Joseph G and Jayaraman, Pradeep Kumar and Wang, Zhengqing and Willis, Karl DD and Furukawa, Yasutaka},
journal = {arXiv preprint arXiv:2401.15563},
year = {2024}
}