HiFi-BRep: High-Fidelity Latent Representation for Robust B-Rep Generation
- URL: http://arxiv.org/abs/2608.16485v2
- Date: Tue, 18 Aug 2026 02:23:14 GMT
- Title: HiFi-BRep: High-Fidelity Latent Representation for Robust B-Rep Generation
- Abstract summary: Boundary representation (B-Rep) generation is a fundamental task in computer-aided design.<n>We propose HiFi-BRep, a novel framework that addresses these limitations through two synergistic contributions.<n>We show that HiFi-BRep significantly outperforms state-of-the-art methods in both structural validity and geometric fidelity.
- Score: 16.881723435082524
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Boundary representation (B-Rep) generation is a fundamental task in computer-aided design, yet the direct synthesis of high-fidelity and structurally valid B-Reps remains a major challenge. Existing deep generative methods suffer from two forms of brittleness: representation brittleness, caused by padding noise and feature contamination in the latent space, and generation brittleness, stemming from sequential error propagation and a train-inference mismatch due to non-differentiable validity enforcement. We propose HiFi-BRep, a novel framework that addresses these limitations through two synergistic contributions. First, a topology-aware encoder constructs a high-fidelity latent representation by eliminating padding via learnable queries and preventing feature contamination with topology-guided attention. Second, a single-stage decoder jointly predicts geometry and topology in parallel, embedding core manifold constraints as a differentiable learning objective. This design ensures mutual guidance between geometry and topology while avoiding cascaded errors. Extensive experiments show that HiFi-BRep significantly outperforms state-of-the-art methods in both structural validity and geometric fidelity, providing a robust solution for high-quality B-Rep synthesis. Code and models are publicly available at https://github.com/1nnoh/HiFi-BRep.
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