SldprtNet: A Large-Scale Multimodal Dataset for CAD Generation in Language-Driven 3D Design
We introduce SldprtNet, a large-scale dataset comprising over 242,000 industrial parts, designed for semantic-driven CAD modeling, geometric deep learning, and the training and fine-tuning of multimodal models for 3D design. The dataset provides 3D models in both .step and .sldprt formats to support diverse training and testing. To enable parametric modeling and facilitate dataset scalability, we developed supporting tools, an encoder and a decoder, which support 13 types of CAD commands and enable lossless transformation between 3D models and a structured text representation. Additionally, each sample is paired with a composite image created by merging seven rendered views from different...
| Authors | Ruogu Li, Sikai Li, Yao Mu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 13 March 2026 |
| Last updated at source | 13 March 2026 |
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