AI RESEARCH
DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces
arXiv CS.AI
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ArXi:2603.05607v1 Announce Type: cross Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets with explicit design histories or boundary representation (BRep) labels. Meanwhile, millions of unannotated 3D meshes remain untapped, limiting progress in scalable CAD generation. To address this, we propose DreamCAD, a multi-modal generative framework that directly produces editable BReps from point-level supervision, without CAD-specific annotations.