Text2CAD: Generating Sequential CAD Designs from Beginner-to-Expert Level Text Prompts
Text2CAD: Designers can efficiently generate parametric CAD models from text prompts. The prompts can vary from abstract shape descriptions to detailed parametric instructions.
We propose Text2CAD as the first AI framework for generating parametric CAD designs using multi-level textual descriptions . Our main contributions are: A Novel Data Annotation Pipeline that leverages open-source LLMs and VLMs to annotate DeepCAD dataset with text prompts containing varying level of complexities and parametric details. Text2CAD Transformer: An end-to-end Transformer based autoregressive architecture for generating CAD design history from input text prompts.
Our data annotation pipeline generates multi-level text prompts describing the construction workflow of a CAD model with varying complexities. We use a two-stage method - Stage 1: Shape description generation using VLM (LlaVA-NeXT). Stage 2: Multi-Level textual annotation generation using LLM (Mixtral-50B).
