Papers › SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operations
SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operations
Pu Li, Jianwei Guo, Xiaopeng Zhang, Dong-Ming Yan
Reverse engineering CAD models from raw geometry is a classic but strenuous research problem. Previous learning-based methods rely heavily on labels due to the supervised design patterns or reconstruct CAD shapes that are not easily editable. In this work, we introduce SECAD-Net, an end-to-end neural network aimed at reconstructing compact and easy-to-edit CAD models in a self-supervised manner. Drawing inspiration from the modeling language that is most commonly used in modern CAD software, we propose to learn 2D sketches and 3D extrusion parameters from raw shapes, from which a set of extrusion cylinders can be generated by extruding each sketch from a 2D plane into a 3D body. By incorporating the Boolean operation (i.e., union), these cylinders can be combined to closely approximate the target geometry. We advocate the use of implicit fields for sketch representation, which allows for creating CAD variations by interpolating latent codes in the sketch latent space. Extensive experiments on both ABC and Fusion 360 datasets demonstrate the effectiveness of our method, and show superiority over state-of-the-art alternatives including the closely related method for supervised CAD reconstruction. We further apply our approach to CAD editing and single-view CAD reconstruction. The code is released at https://github.com/BunnySoCrazy/SECAD-Net.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| CAD Reconstruction | DeepCAD | SECAD-Net | Camfer Distance (median) | 3.65 | #6 of 11 | Archive leaderboard | report |
| CAD Reconstruction | DeepCAD | SECAD-Net | IoU | 72.9 | #6 of 11 | Archive leaderboard | report |
| CAD Reconstruction | Fusion 360 Gallery | SECAD-Net | Chamfer Distance (median) | 4.32 | #3 of 11 | Archive leaderboard | report |
| CAD Reconstruction | Fusion 360 Gallery | SECAD-Net | IoU | 69.0 | #3 of 11 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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