mlsanityData to 14 Oct 2026

ABC: A Big CAD Model Dataset For Geometric Deep Learning

arXiv 1812.06216 ↗First posted 15 Dec 2018cs.GR cs.CG cs.CVcited by 341

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Abstract (arXiv)

We introduce ABC-Dataset, a collection of one million Computer-Aided Design (CAD) models for research of geometric deep learning methods and applications. Each model is a collection of explicitly parametrized curves and surfaces, providing ground truth for differential quantities, patch segmentation, geometric feature detection, and shape reconstruction. Sampling the parametric descriptions of surfaces and curves allows generating data in different formats and resolutions, enabling fair comparisons for a wide range of geometric learning algorithms. As a use case for our dataset, we perform a large-scale benchmark for estimation of surface normals, comparing existing data driven methods and evaluating their performance against both the ground truth and traditional normal estimation methods.

Key facts. Cited by 341 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Dec 2018.

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Citing papers per year: 2021: 34; 2022: 44; 2023: 44; 2024: 59; 2025: 78; 2026: 82.

341 papers.

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  1. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
  2. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  3. 2022Kubric: A scalable dataset generatorcited by 381
  4. 2021ABO: Dataset and Benchmarks for Real-World 3D Object Understandingcited by 366
  5. 2021DeepCAD: A Deep Generative Network for Computer-Aided Design Modelscited by 271
  6. 2023MVImgNet: A Large-scale Dataset of Multi-view Imagescited by 220
  7. 2021Frame Averaging for Invariant and Equivariant Network Designcited by 168
  8. 2021Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Biascited by 118
  9. 2023Neural Kernel Surface Reconstructioncited by 104
  10. 2024BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometrycited by 103
  11. 2021BRepNet: A topological message passing system for solid modelscited by 95
  12. 2025PARTFIELD: Learning 3D Feature Fields for Part Segmentation and Beyondcited by 95
38 more
  1. 2022POCO: Point Convolution for Surface Reconstructioncited by 92
  2. 2021Computer-Aided Design as Languagecited by 82
  3. 2022AKB-48: A Real-World Articulated Object Knowledge Basecited by 82
  4. 2024CAD-MLLM: Unifying Multimodality-Conditioned CAD Generation With MLLMcited by 81
  5. 2022SolidGen: An Autoregressive Model for Direct B-rep Synthesiscited by 80
  6. 2021JoinABLe: Learning Bottom-up Assembly of Parametric CAD Jointscited by 78
  7. 2022Neural Dual Contouringcited by 71
  8. 2021SketchGen: Generating Constrained CAD Sketchescited by 68
  9. 2022ALSO: Automotive Lidar Self-supervision by Occupancy estimationcited by 68
  10. 2025CAD-Llama: Leveraging Large Language Models for Computer-Aided Design Parametric 3D Model Generationcited by 67
  11. 2024CAD-Recode: Reverse Engineering CAD Code from Point Cloudscited by 66
  12. 2021CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assemblycited by 62
  13. 2021Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinderscited by 60
  14. 2022Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priorscited by 60
  15. 2022Surface Reconstruction from Point Clouds by Learning Predictive Context Priorscited by 54
  16. 2023NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotationscited by 53
  17. 2021Neural Marching Cubescited by 50
  18. 2023SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operationscited by 46
  19. 2025Text-to-CadQuery: A New Paradigm for CAD Generation with Scalable Large Model Capabilitiescited by 43
  20. 2025CAD-Coder: An Open-Source Vision-Language Model for Computer-Aided Design Code Generationcited by 43
  21. 2022Surface Reconstruction from Point Clouds: A Survey and a Benchmarkcited by 41
  22. 2022Reconstructing editable prismatic CAD from rounded voxel modelscited by 41
  23. 20223DALL-E: Integrating Text-to-Image AI in 3D Design Workflowscited by 41
  24. 2023D2CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropoutscited by 40
  25. 2024GenCAD: Image-Conditioned Computer-Aided Design Generation with Transformer-Based Contrastive Representation and Diffusion Priorscited by 38
  26. 2021HPNet: Deep Primitive Segmentation Using Hybrid Representationscited by 36
  27. 2023Point2CAD: Reverse Engineering CAD Models from 3D Point Cloudscited by 36
  28. 2023Neural-Singular-Hessian: Implicit Neural Representation of Unoriented Point Clouds by Enforcing Singular Hessiancited by 35
  29. 2024Img2CAD: Reverse Engineering 3D CAD Models from Images through VLM-Assisted Conditional Factorizationcited by 35
  30. 2024Can Large Language Models Understand Symbolic Graphics Programs?cited by 35
  31. 2021Active 3D Shape Reconstruction from Vision and Touchcited by 34
  32. 2021PC2WF: 3D Wireframe Reconstruction from Raw Point Cloudscited by 33
  33. 2022RTMV: A Ray-Traced Multi-View Synthetic Dataset for Novel View Synthesiscited by 33
  34. 2022CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representationscited by 31
  35. 2025HoLa: B-Rep Generation using a Holistic Latent Representationcited by 30
  36. 2024TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Cloudscited by 29
  37. 2024Make-A-Shape: a Ten-Million-scale 3D Shape Modelcited by 25
  38. 2025CADDreamer: CAD Object Generation from Single-view Imagescited by 25

50 most cited of 341 All 341 (JSON)