mlsanityData to 7 Oct 2026

ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsing

arXiv 2209.15632 ↗First posted 30 Sep 2022cs.CV cs.GRcited by 38

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Abstract (arXiv)

Sketch-and-extrude is a common and intuitive modeling process in computer aided design. This paper studies the problem of learning the shape given in the form of point clouds by inverse sketch-and-extrude. We present ExtrudeNet, an unsupervised end-to-end network for discovering sketch and extrude from point clouds. Behind ExtrudeNet are two new technical components: 1) an effective representation for sketch and extrude, which can model extrusion with freeform sketches and conventional cylinder and box primitives as well; and 2) a numerical method for computing the signed distance field which is used in the network learning. This is the first attempt that uses machine learning to reverse engineer the sketch-and-extrude modeling process of a shape in an unsupervised fashion. ExtrudeNet not only outputs a compact, editable and interpretable representation of the shape that can be seamlessly integrated into modern CAD software, but also aligns with the standard CAD modeling process facilitating various editing applications, which distinguishes our work from existing shape parsing research. Code is released at https://github.com/kimren227/ExtrudeNet.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). Builds on 20 of its 40 references that are in the map. First posted on arXiv 30 Sep 2022.

Builds on

20 of 40 references.

References · 20

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  4. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  5. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  6. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  7. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,220
  8. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  9. 2021DeepCAD: A Deep Generative Network for Computer-Aided Design Modelscited by 266
  10. 2019BSP-Net: Generating Compact Meshes via Binary Space Partitioningcited by 205
  11. 2016Learning Shape Abstractions by Assembling Volumetric Primitivescited by 181
  12. 2019CvxNet: Learnable Convex Decompositioncited by 173
8 more
  1. 2019Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboidscited by 123
  2. 2017CSGNet: Neural Shape Parser for Constructive Solid Geometrycited by 106
  3. 2020DualSDF: Semantic Shape Manipulation using a Two-Level Representationcited by 82
  4. 2021Computer-Aided Design as Languagecited by 82
  5. 2020UCSG-Net -- Unsupervised Discovering of Constructive Solid Geometry Treecited by 77
  6. 2021SketchGen: Generating Constrained CAD Sketchescited by 68
  7. 2021CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assemblycited by 62
  8. 2021CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsingcited by 51

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 9; 2024: 13; 2025: 8; 2026: 8.

38 papers.

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  1. 2024BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometrycited by 101
  2. 2023Hierarchical Neural Coding for Controllable CAD Model Generationcited by 84
  3. 2024CAD-MLLM: Unifying Multimodality-Conditioned CAD Generation With MLLMcited by 74
  4. 2025CAD-Llama: Leveraging Large Language Models for Computer-Aided Design Parametric 3D Model Generationcited by 65
  5. 2024CAD-Recode: Reverse Engineering CAD Code from Point Cloudscited by 63
  6. 2024CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attentioncited by 62
  7. 2023SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operationscited by 46
  8. 2023D2CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropoutscited by 39
  9. 2024Img2CAD: Conditioned 3D CAD Model Generation from Single Image with Structured Visual Geometrycited by 35
  10. 2024Img2CAD: Reverse Engineering 3D CAD Models from Images through VLM-Assisted Conditional Factorizationcited by 34
  11. 2024Can Large Language Models Understand Symbolic Graphics Programs?cited by 32
  12. 2024TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Cloudscited by 29
26 more
  1. 2025HoLa: B-Rep Generation using a Holistic Latent Representationcited by 29
  2. 2023ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitivescited by 22
  3. 2025Seek-CAD: A Self-refined Generative Modeling for 3D Parametric CAD Using Local Inference via DeepSeekcited by 22
  4. 2025cadrille: Multi-modal CAD Reconstruction with Reinforcement Learningcited by 14
  5. 2023Iterative Superquadric Recomposition of 3D Objects from Multiple Viewscited by 13
  6. 2026Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generationcited by 11
  7. 2023Improving Unsupervised Visual Program Inference with Code Rewriting Familiescited by 10
  8. 2024SweepNet: Unsupervised Learning Shape Abstraction via Neural Sweeperscited by 5
  9. 2025Point2Primitive: CAD Reconstruction from Point Cloud by Direct Primitive Predictioncited by 4
  10. 2025MiCADangelo: Fine-Grained Reconstruction of Constrained CAD Models from 3D Scanscited by 4
  11. 2026CADReasoner: Iterative Program Editing for CAD Reverse Engineeringcited by 4
  12. 2023A Review of Deep Learning-Powered Mesh Reconstruction Methodscited by 3
  13. 2023A Survey of Methods for Converting Unstructured Data to CSG Modelscited by 3
  14. 2023CNC-Net: Self-Supervised Learning for CNC Machining Operationscited by 3
  15. 2024MV2Cyl: Reconstructing 3D Extrusion Cylinders from Multi-View Imagescited by 3
  16. 2026CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimizationcited by 3
  17. 2025Target-Guided Bayesian Flow Networks for Quantitatively Constrained CAD Generationcited by 2
  18. 2024PS-CAD: Local Geometry Guidance via Prompting and Selection for CAD Reconstructioncited by 1
  19. 2024Differentiable Convex Polyhedra Optimization from Multi-view Imagescited by 1
  20. 2026DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfacescited by 1
  21. 2024Pattern Analogies: Learning to Perform Programmatic Image Edits by Analogycited by 0
  22. 2025CADMorph: Geometry-Driven Parametric CAD Editing via a Plan-Generate-Verify Loopcited by 0
  23. 2026GeoFusion-CAD: Structure-Aware Diffusion with Geometric State Space for Parametric 3D Designcited by 0
  24. 2026Best Segmentation Buddies for Image-Shape Correspondencecited by 0
  25. 2026CADENA: Stepwise CAD Reverse Engineeringcited by 0
  26. 2026VGGT-CAD: Reconstructing Parametric CAD 3D Model with Geometric Groundingcited by 0