OmniMech: All-in-one Multimodal Mechanical Benchmark for 3D Reconstruction
- URL: http://arxiv.org/abs/2608.05539v1
- Date: Thu, 06 Aug 2026 02:36:22 GMT
- Title: OmniMech: All-in-one Multimodal Mechanical Benchmark for 3D Reconstruction
- Abstract summary: We introduce OmniMech, the first million-scale benchmark for evaluating vision-language models on CAD generation from industrial data.<n> OmniMech contains more than 251,000 fully dimensioned and toleranced 2D orthographic drawings, paired with native CAD models.<n>We will release the benchmark data, evaluation code, and tool interfaces to support future research.
- Score: 15.427717696810456
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Recent vision-language models (VLMs) can generate executable CAD programs from images, but existing methods mainly target coarse, general-purpose 3D objects and rarely address the fine-grained geometry and millimeter-level tolerances required in industrial mechanical design. We introduce OmniMech, the first million-scale benchmark for evaluating VLMs on executable CAD generation from industrial manufacturing data. OmniMech contains more than 251,000 fully dimensioned and toleranced 2D orthographic drawings, paired with native CAD models, multi-view renderings, mesh, STEP and B-rep representations, and rich semantic annotations. The benchmark includes four tasks: (1) parametric CAD program synthesis from engineering drawings; (2) diagram-to-3D reasoning for geometrically and structurally consistent reconstruction; (3) annotation-grounded reasoning over dimensions, symbols, feature callouts, and manufacturing constraints; and (4) tool-augmented agentic reasoning using visualization, measurement, CAD execution, and verification tools. Experiments show that current VLMs and CAD-specialized models still struggle with executable program synthesis, fine-grained 3D reconstruction, and reliable enforcement of dimensions and tolerances. We will release the benchmark data, evaluation code, and tool interfaces to support future research.
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