mlsanityData to 7 Oct 2026

SketchGen: Generating Constrained CAD Sketches

arXiv 2106.02711 ↗First posted 4 Jun 2021cs.LG cs.AI cs.CVcited by 68

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Abstract (arXiv)

Computer-aided design (CAD) is the most widely used modeling approach for technical design. The typical starting point in these designs is 2D sketches which can later be extruded and combined to obtain complex three-dimensional assemblies. Such sketches are typically composed of parametric primitives, such as points, lines, and circular arcs, augmented with geometric constraints linking the primitives, such as coincidence, parallelism, or orthogonality. Sketches can be represented as graphs, with the primitives as nodes and the constraints as edges. Training a model to automatically generate CAD sketches can enable several novel workflows, but is challenging due to the complexity of the graphs and the heterogeneity of the primitives and constraints. In particular, each type of primitive and constraint may require a record of different size and parameter types. We propose SketchGen as a generative model based on a transformer architecture to address the heterogeneity problem by carefully designing a sequential language for the primitives and constraints that allows distinguishing between different primitive or constraint types and their parameters, while encouraging our model to re-use information across related parameters, encoding shared structure. A particular highlight of our work is the ability to produce primitives linked via constraints that enables the final output to be further regularized via a constraint solver. We evaluate our model by demonstrating constraint prediction for given sets of primitives and full sketch generation from scratch, showing that our approach significantly out performs the state-of-the-art in CAD sketch generation.

Key facts. Cited by 68 papers in the map (data through 7 Oct 2026). Builds on 33 of its 42 references that are in the map. First posted on arXiv 4 Jun 2021.

Builds on

33 of 42 references.

References · 33

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21 more
  1. 2017CSGNet: Neural Shape Parser for Constructive Solid Geometrycited by 106
  2. 2020ParSeNet: A Parametric Surface Fitting Network for 3D Point Cloudscited by 96
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  15. 2021Inferring CAD Modeling Sequences Using Zone Graphscited by 50
  16. 2021Engineering Sketch Generation for Computer-Aided Designcited by 49
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 12; 2023: 10; 2024: 17; 2025: 12; 2026: 15.

68 papers.

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  1. 2022SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebookscited by 121
  2. 2024SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Modelcited by 95
  3. 2023Hierarchical Neural Coding for Controllable CAD Model Generationcited by 84
  4. 2022SolidGen: An Autoregressive Model for Direct B-rep Synthesiscited by 78
  5. 2021Vitruvion: A Generative Model of Parametric CAD Sketchescited by 66
  6. 2024A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languagescited by 65
  7. 2021Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinderscited by 59
  8. 2022Reconstructing editable prismatic CAD from rounded voxel modelscited by 41
  9. 2023D2CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropoutscited by 39
  10. 2022ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsingcited by 38
  11. 2024Graphic Design with Large Multimodal Modelcited by 38
  12. 2023PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Modelscited by 36
38 more
  1. 2024GenCAD: Image-Conditioned Computer-Aided Design Generation with Transformer-Based Contrastive Representation and Diffusion Priorscited by 36
  2. 2024Img2CAD: Reverse Engineering 3D CAD Models from Images through VLM-Assisted Conditional Factorizationcited by 34
  3. 2022CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representationscited by 30
  4. 2024CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketchescited by 28
  5. 2022Self-Supervised Representation Learning for CADcited by 22
  6. 2023ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitivescited by 22
  7. 2024Text2CAD: Generating Sequential CAD Models from Beginner-to-Expert Level Text Promptscited by 22
  8. 2025Seek-CAD: A Self-refined Generative Modeling for 3D Parametric CAD Using Local Inference via DeepSeekcited by 22
  9. 2024Large Language Model Agent as a Mechanical Designercited by 20
  10. 2022Neural Face Identification in a 2D Wireframe Projection of a Manifold Objectcited by 18
  11. 2022ComplexGen: CAD Reconstruction by B-Rep Chain Complex Generationcited by 17
  12. 2024Design2GarmentCode: Turning Design Concepts to Tangible Garments Through Program Synthesiscited by 17
  13. 2022Abstracting Sketches through Simple Primitivescited by 14
  14. 2024Geometric Deep Learning for Computer-Aided Design: A Surveycited by 14
  15. 2023AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designscited by 13
  16. 2025BrepGPT: Autoregressive B-rep Generation with Voronoi Half-Patchcited by 12
  17. 2023Constraining Generative Models for Engineering Design with Negative Datacited by 11
  18. 2022Discovering Design Concepts for CAD Sketchescited by 10
  19. 2024PICASSO: A Feed-Forward Framework for Parametric Inference of CAD Sketches via Rendering Self-Supervisioncited by 9
  20. 2024Freehand Sketch Generation from Mechanical Componentscited by 8
  21. 2025Aligning Constraint Generation with Design Intent in Parametric CADcited by 8
  22. 2025CAD-Coder:Text-Guided CAD Files Code Generationcited by 8
  23. 2024Parametric Primitive Analysis of CAD Sketches with Vision Transformercited by 7
  24. 2025GenCAD-3D: CAD Program Generation using Multimodal Latent Space Alignment and Synthetic Dataset Balancingcited by 7
  25. 2026CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generationcited by 7
  26. 2024DAVINCI: A Single-Stage Architecture for Constrained CAD Sketch Inferencecited by 6
  27. 2023Architext: Language-Driven Generative Architecture Designcited by 5
  28. 2025MiCADangelo: Fine-Grained Reconstruction of Constrained CAD Models from 3D Scanscited by 4
  29. 2024MV2Cyl: Reconstructing 3D Extrusion Cylinders from Multi-View Imagescited by 3
  30. 2025WIR3D: Visually-Informed and Geometry-Aware 3D Shape Abstractioncited by 3
  31. 2026BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoningcited by 3
  32. 2026ArtisanCAD: An Industrial-Level CAD Agent with Expert-Grounded Knowledge Distillationcited by 3
  33. 2022Design of Unmanned Air Vehicles Using Transformer Surrogate Modelscited by 2
  34. 2024Historical Astronomical Diagrams Decomposition in Geometric Primitivescited by 2
  35. 2025Target-Guided Bayesian Flow Networks for Quantitatively Constrained CAD Generationcited by 2
  36. 2026Logic Tensor Network-Enhanced Generative Adversarial Networkcited by 2
  37. 2026SldprtNet: A Large-Scale Multimodal Dataset for CAD Generation in Language-Driven 3D Designcited by 2
  38. 2026Autoregressive B-Rep Shape Generation with Parametric Surfacescited by 2

50 most cited of 68 All 68 (JSON)