flâneur

[2605.10873] CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation

arxiv.org · 7,545 words · saved by 1 readers

Abstract:Recovering editable CAD programs from images or 3D observations is central to AI-assisted design, but progress is difficult to measure because existing evaluations are fragmented across datasets, modalities, and metrics. We introduce CADBench, a unified benchmark for multimodal CAD program generation. CADBench contains 18,000 evaluation samples spanning six benchmark families derived from DeepCAD, Fusion 360, ABC, MCB, and Objaverse; five input modalities including clean meshes, noisy meshes, single-view renders, photorealistic renders, and multi-view renders; and six metrics covering geometric fidelity, executability, and program compactness. STEP-based families are stratified by B-rep face count and all families are diversity-sampled to support controlled analysis across complexity and object variation. We benchmark eleven CAD-specialized and general-purpose vision-language systems, generating more than 1.4 million CAD programs. Under idealized inputs, specialized mesh-to-CAD models substantially outperform code-generating VLMs, which remain far from reliable CAD program reconstruction. CADBench further reveals three recurring failure modes: reconstruction quality degrades with geometric complexity, CAD-specialized models can be brittle under modality shift, and model rankings change across metrics. Together, these results position CADBench as a diagnostic testbed for measuring progress in editable 3D reconstruction and multimodal CAD understanding. The benchmark is publicly available at this https URL.

C AD B ENCH: A Multimodal Benchmark for AI-Assisted CAD Program Generation Anna C. Doris Jacob Thomas Sony Ghadi Nehme Era Syla Amin Heyrani Nobari Faez Ahmed Massachusetts Institute of Technology arXiv:2605.10873v2 [cs.CV] 18 Jun 2026…

saved by

related reading