BrepGen: A B-rep Generative Diffusion Model with Structured Latent
  Geometry
Xiang Xu Joseph G. Lambourne Pradeep Kumar Jayaraman Zhengqing Wang Karl D. D. Willis Yasutaka Furukawa
This paper presents BrepGen, a diffusion-based generative approach that
directly outputs a Boundary representation (B-rep) Computer-Aided Design (CAD)
model. BrepGen represents a B-rep model as a novel structured latent geometry
in a hierarchical tree. With the root node representing a whole CAD solid, each
element of a B-rep model (i.e., a face, an edge, or a vertex) progressively
turns into a child-node from top to bottom. B-rep geometry information goes
into the nodes as the global bounding box of each primitive along with a latent
code describing the local geometric shape. The B-rep topology information is
implicitly represented by node duplication. When two faces share an edge, the
edge curve will appear twice in the tree, and a T-junction vertex with three
incident edges appears six times in the tree with identical node features.
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 sets a new milestone in
CAD B-rep generation, surpassing existing methods on various benchmarks.
Results on our newly collected furniture dataset further showcase its
exceptional capability in generating complicated geometry. While previous
methods were limited to generating simple prismatic shapes, BrepGen
incorporates free-form and doubly-curved surfaces for the first time.
Additional applications of BrepGen include CAD autocomplete and design
interpolation. The code, pretrained models, and dataset will be released.