hugging-apps/hifi-brep-generation

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

This Space demonstrates unconditional generation of 3D B-Rep CAD structures using the HiFi-BRep diffusion model.

How it works

1. 1.A DiT (Diffusion Transformer) model generates latent representations via DDIM sampling
2. 2.A VAE decoder transforms latents into B-spline surface/edge control points, bounding boxes, and face-edge adjacency predictions
3. 3.The geometry is reconstructed as a 3D point cloud and mesh for visualization

Model

• —Weights: 1nnoh/HiFi-BRep
• —Variant: DeepCAD 4-30 (4-30 faces range)
• —Code: github.com/1nnoh/HiFi-BRep

Note

The original reconstruction pipeline uses OpenCascade (pythonocc-core) for full B-Rep solid construction and STEP file export. Since pythonocc-core is conda-only and not pip-installable on Hugging Face Spaces, this demo reconstructs the geometry using pure numpy B-spline evaluation and displays it as a 3D mesh. The diffusion + decoder pipeline runs identically to the original code.