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arXiv · 2604.02847

HiDiGen: Hierarchical Diffusion for B-Rep Generation with Explicit Topological Constraints

Shurui Liu·Weide Chen·Ancong Wu
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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 two-stage topological modeling ensures high validity. Experimental results show that HiDiGen achieves strong performance, generating novel, diverse, and topologically sound CAD models.

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Shurui Liu, Weide Chen, Ancong Wu. 2026-04-03. HiDiGen: Hierarchical Diffusion for B-Rep Generation with Explicit Topological Constraints. https://arxiv.org/abs/2604.02847

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