Research map / Graph learning / Graph algorithms and clustering
Inferring CAD Modeling Sequences Using Zone Graphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use zone-graph sketch + extrude search instead of primitive CSG inference | InverseCSG test set · all models | median reconstruction error (%): 0.88 -> 0.72 | Helped |
| use zone-graph sketch + extrude search instead of primitive CSG inference | InverseCSG test set · all models | median search time (s): 900 -> 242 | Helped |
| use zone-graph sketch + extrude search instead of primitive CSG inference | InverseCSG test set · sketch + extrude models | median reconstruction error (%): 0.79 -> 0.23 | Helped |
| use zone-graph sketch + extrude search instead of primitive CSG inference | InverseCSG test set · sketch + extrude models | median search time (s): 900 -> 242 | Helped |
| use network guidance instead of heuristic guidance | CAD sequence inference · InverseCSG test set, all models | median reconstruction error (%): 0.50 -> 0.72 | Hurt |
| use network guidance instead of heuristic guidance | CAD sequence inference · InverseCSG test set, all models | median search time (s): 197 -> 242 | Hurt |
| use network guidance instead of InverseCSG inference | CAD sequence inference · CAD expert study, InverseCSG comparison | % chosen: 84.7% | Helped |
| use learned network guidance instead of heuristic guidance | CAD sequence inference · CAD expert study, Ours Heur comparison | % chosen: 41.0% | Mixed |
| increase extrusion proposal level from 1 to 3 (ablation) | Zone graph search · Fusion 360 Gallery | ground-truth sequence coverage (%): 60% -> 63% | Helped |
| increase extrusion proposal level from 1 to 3 (ablation) | Zone graph search · Fusion 360 Gallery | reconstruction coverage (%): 80% -> 80% | No clear effect |
| remove zone graph simplification (ablation) | Zone graph search · Fusion 360 Gallery | reconstruction coverage (%): 80% -> 82% | Helped |
Closest papers by meaning
- MiCADangelo: Fine-Grained Reconstruction of Constrained CAD Models from 3D Scans (NeurIPS 2025 · similarity 0.87)
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- SpelsNet: Surface Primitive Elements Segmentation by B-Rep Graph Structure Supervision (NeurIPS 2024 · similarity 0.86)
- From 2D CAD Drawings to 3D Parametric Models: A Vision-Language Approach (AAAI 2025 · similarity 0.86)
- Point2CAD: Reverse Engineering CAD Models from 3D Point Clouds (CVPR 2024 · similarity 0.86)
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