| title | HiFi-BRep: High-Fidelity Latent Representation for Robust B-Rep Generation |
|---|---|
| authors | Junhao Hou, Chenqi Luo, Pufan Wang, Jiaying Lu, Yusheng Liu, Feiwei Qin, Meie Fang, Kun Zhou |
| date | 2026-08-17 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2608.16485 |
| upvotes | 1 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf code |
| 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. |
cite
@misc{hou2026hifi,
title={HiFi-BRep: High-Fidelity Latent Representation for Robust B-Rep Generation},
author={Junhao Hou and Chenqi Luo and Pufan Wang and Jiaying Lu and Yusheng Liu and Feiwei Qin and Meie Fang and Kun Zhou},
year={2026},
eprint={2608.16485},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2608.16485}
}