CADReview: Automatically Reviewing CAD Programs with Error Detection and Correction
This addresses the time-consuming manual review process in CAD design workflows, though it appears incremental as it builds on existing multimodal models with a domain-specific focus.
The paper tackles the problem of automating error detection and correction in CAD programs to ensure consistency with reference images, introducing the ReCAD framework that significantly outperforms existing multimodal large language models on a dataset of over 20K program-image pairs.
Computer-aided design (CAD) is crucial in prototyping 3D objects through geometric instructions (i.e., CAD programs). In practical design workflows, designers often engage in time-consuming reviews and refinements of these prototypes by comparing them with reference images. To bridge this gap, we introduce the CAD review task to automatically detect and correct potential errors, ensuring consistency between the constructed 3D objects and reference images. However, recent advanced multimodal large language models (MLLMs) struggle to recognize multiple geometric components and perform spatial geometric operations within the CAD program, leading to inaccurate reviews. In this paper, we propose the CAD program repairer (ReCAD) framework to effectively detect program errors and provide helpful feedback on error correction. Additionally, we create a dataset, CADReview, consisting of over 20K program-image pairs, with diverse errors for the CAD review task. Extensive experiments demonstrate that our ReCAD significantly outperforms existing MLLMs, which shows great potential in design applications.