BrepGPT: Autoregressive B-rep Generation with Voronoi Half-Patch
- URL: http://arxiv.org/abs/2511.22171v1
- Date: Thu, 27 Nov 2025 07:16:53 GMT
- Title: BrepGPT: Autoregressive B-rep Generation with Voronoi Half-Patch
- Abstract summary: Boundary representation (B-rep) is the de facto standard for CAD model representation in modern industrial design.<n>We present BrepGPT, a single-stage autoregressive framework for B-rep generation.
- Score: 61.20046418942948
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Boundary representation (B-rep) is the de facto standard for CAD model representation in modern industrial design. The intricate coupling between geometric and topological elements in B-rep structures has forced existing generative methods to rely on cascaded multi-stage networks, resulting in error accumulation and computational inefficiency. We present BrepGPT, a single-stage autoregressive framework for B-rep generation. Our key innovation lies in the Voronoi Half-Patch (VHP) representation, which decomposes B-reps into unified local units by assigning geometry to nearest half-edges and sampling their next pointers. Unlike hierarchical representations that require multiple distinct encodings for different structural levels, our VHP representation facilitates unifying geometric attributes and topological relations in a single, coherent format. We further leverage dual VQ-VAEs to encode both vertex topology and Voronoi Half-Patches into vertex-based tokens, achieving a more compact sequential encoding. A decoder-only Transformer is then trained to autoregressively predict these tokens, which are subsequently mapped to vertex-based features and decoded into complete B-rep models. Experiments demonstrate that BrepGPT achieves state-of-the-art performance in unconditional B-rep generation. The framework also exhibits versatility in various applications, including conditional generation from category labels, point clouds, text descriptions, and images, as well as B-rep autocompletion and interpolation.
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