CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimization
Ghadi Nehme, Eamon Whalen, Faez Ahmed

TL;DR
CADFit is a hybrid optimization framework that accurately reconstructs complex, editable CAD models from meshes, outperforming existing methods in accuracy and validity, and enabling end-to-end image-to-CAD reconstruction.
Contribution
It introduces a novel IoU-driven optimization approach supporting diverse CAD operations, significantly improving reconstruction quality for complex designs.
Findings
Outperforms state-of-the-art mesh-to-CAD methods in volumetric IoU and Chamfer Distance.
Reduces the Invalid Ratio of reconstructed CAD programs, especially for complex models.
Enables end-to-end CAD reconstruction from images by combining geometry and CAD fitting.
Abstract
Despite recent progress, recovering parametric CAD construction sequences from geometric input, such as meshes or point clouds, is a key challenge for design and manufacturing, as existing CAD reconstruction and generation methods are largely restricted to difficult-to-edit formats like meshes or Breps or editable simple sketch-and-extrude pipelines and low-complexity datasets. We introduce CADFit, a hybrid optimization-based CAD reconstruction framework that recovers complex, editable CAD construction sequences from meshes by incrementally fitting and validating parametric operations using geometric feedback. Our approach is distinguished by formulating reconstruction as an IoU-driven optimization over structured CAD programs and supporting a rich set of operations, including extrusions, revolutions, fillets, and chamfers. Experiments on multiple CAD benchmarks show that CADFit…
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