HiFi-BRep: High-Fidelity Latent Representation for Robust B-Rep Generation

Key points

It separates faces and edges for processing but lets them exchange information only for pairs that are actually connected, and it creates a compact representation with 48 learnable queries whose input length does not depend on the number of parts.
After duplicate removal and complexity filtering, it trained on 83,611 DeepCAD shapes and 186,148 ABC shapes, and Valid here means the share that passes STEP export, watertight closure, and manifold connectivity checks.
For unconditional generation, Valid is 72.20 percent on DeepCAD and 32.66 percent on ABC, which is higher than DTGBrepGen's 43.20 percent and 24.88 percent, but DTGBrepGen is better on ABC distribution metrics such as COV, MMD-CD, and JSD.
On DeepCAD reconstruction, the full model reaches 95.2 percent Valid; when it first reconstructs the shape and only then predicts the connectivity, the score drops to 69.3 percent, and the non-parallel generation time is 3.83 seconds per shape.
It supports only closed solids and a fixed maximum number of faces and edges, and it still leaves cut faces, mismatched joints, thin faces, and self-intersections, with exact intersection and trimming left to the CAD kernel.

External research summaries. These are not HDATF publications or measured product results.