{"url":"/dataset/text2cad","name":"Text2CAD","full_name":"Text2CAD","description_markdown":"Prototyping complex computer-aided design (CAD) models in modern softwares can be very time-consuming. This is due to the lack of intelligent systems that can quickly generate simpler intermediate parts. We propose Text2CAD, the first AI framework for generating text-to-parametric CAD models using designer-friendly instructions for all skill levels. Furthermore, we introduce a data annotation pipeline for generating text prompts based on natural language instructions for the DeepCAD dataset using Mistral and LLaVA-NeXT. The dataset contains $\\sim170$K models and $\\sim660$K text annotations, from abstract CAD descriptions (e.g., \\textit{generate two concentric cylinders}) to detailed specifications (e.g., \\textit{draw two circles with center} $(x,y)$ \\textit{and radius} $r_{1}$, $r_{2}$, \\textit{and extrude along the normal by} $d$...). Within the Text2CAD framework, we propose an end-to-end transformer-based auto-regressive network to generate parametric CAD models from input texts. We evaluate the performance of our model through a mixture of metrics, including visual quality, parametric precision, and geometrical accuracy. Our proposed framework shows great potential in AI-aided design applications. Project page is available at~\\href{https://sadilkhan.github.io/text2cad-project/}{https://sadilkhan.github.io/text2cad-project/}.","description_withheld":null,"homepage":"https://sadilkhan.github.io/text2cad-project/","introduced_date":"2024-09-25","introduced_date_note":null,"introduced_by":{"paper":"/paper/text2cad-generating-sequential-cad-models","title":"Text2CAD: Generating Sequential CAD Models from Beginner-to-Expert Level Text Prompts","first_author":"Mohammad Sadil Khan","url":null},"license":{"name":"cc-by-nc-sa-4.0","url":"https://huggingface.co/datasets/SadilKhan/Text2CAD"},"modalities":[],"tasks":[{"name":"CAD Reconstruction","url":"/task/cad-reconstruction","datasets_with_task":"/datasets/task/cad-reconstruction"},{"name":"Text to 3D","url":"/task/text-to-3d","datasets_with_task":"/datasets/task/text-to-3d"}],"languages":[],"variants":["Text2CAD"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}