分离拓扑与几何生成，提升CAD模型的结构正确性和细节精度
DTGBrepGen: A Novel B-rep Generative Model through Decoupling Topology and Geometry
- 先分步生成拓扑结构，再用扩散模型逐步构建几何形状
- 在多个CAD数据集上拓扑有效率更高，生成结果更真实多样
- 适合需要高精度几何建模的工业设计与自动化建模场景
边界表示（B-rep）是计算机辅助设计（CAD）中的基础几何格式。然而，由于拓扑与几何之间的复杂耦合关系，自动生成合法且高质量的B-rep模型仍具挑战性。现有方法多侧重几何表达，忽视拓扑约束，难以保证结构有效性与几何准确性。本文提出DTGBrepGen，一种拓扑-几何解耦的B-rep生成框架，显式处理二者关系。首先通过两阶段过程独立建模边-面与边-顶点邻接关系，生成合法拓扑结构；随后采用基于Transformer的扩散模型，按序生成顶点坐标、边几何及面几何（以B样条表示）。在多个CAD数据集上的实验表明，该方法显著优于现有方法，在拓扑有效性与几何精度上均有提升，生成结果更具多样性与真实性。代码已公开于https://github.com/jinli99/DTGBrepGen。
原文摘要 · Abstract (English)
Boundary representation (B-rep) of geometric models is a fundamental format in Computer-Aided Design (CAD). However, automatically generating valid and high-quality B-rep models remains challenging due to the complex interdependence between the topology and geometry of the models. Existing methods tend to prioritize geometric representation while giving insufficient attention to topological constraints, making it difficult to maintain structural validity and geometric accuracy. In this paper, we propose DTGBrepGen, a novel topology-geometry decoupled framework for B-rep generation that explicitly addresses both aspects. Our approach first generates valid topological structures through a two-stage process that independently models edge-face and edge-vertex adjacency relationships. Subsequently, we employ Transformer-based diffusion models for sequential geometry generation, progressively generating vertex coordinates, followed by edge geometries and face geometries which are represented as B-splines. Extensive experiments on diverse CAD datasets show that DTGBrepGen significantly outperforms existing methods in both topological validity and geometric accuracy, achieving higher validity rates and producing more diverse and realistic B-reps. Our code is publicly available at https://github.com/jinli99/DTGBrepGen.
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