HiDiGen: Hierarchical Diffusion for B-Rep Generation with Explicit Topological Constraints
Year: 2026
Type: conference-paper
Abstract: Boundary representation ($B$-rep) is the standard 3D modeling format in CAD systems, encoding both geometric primitives and topological connectivity. Despite its prevalence, deep generative modeling of valid$B$-rep structures remains challenging due to the intricate interplay between discrete topology and continuous geometry. In this paper, we propose HiDiGen, a hierarchical generation framework that decouples geometry modeling into two stages, each guided by explicitly modeled topological constraints. Specifically, our approach first establishes face-edge incidence relations to define a coherent topological scaffold, upon which face proxies and initial edge curves are generated. Subsequently, multiple Transformer-based diffusion modules are employed to refine the geometry by generating precise face surfaces and vertex positions, with edge-vertex adjacencies dynamically established and enforced to preserve structural consistency. This progressive geometry hierarchy enables the generation of more novel and diverse shapes, while twostage topological modeling ensures high validity. Experimental results show that HiDiGen achieves strong performance, generating novel, diverse, and topologically sound CAD models.
Authors: Shurui Liu, Weide Chen, Ancong Wu
Institution: Sun Yat-sen University
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W7220929092