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https://github.com/bertjiazheng/awesome-CAD
😎 A list of awesome Computer-Aided Design (CAD) papers
https://github.com/bertjiazheng/awesome-CAD
List: awesome-CAD
awesome cad computer-vision deep-learning
Last synced: 16 days ago
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😎 A list of awesome Computer-Aided Design (CAD) papers
- Host: GitHub
- URL: https://github.com/bertjiazheng/awesome-CAD
- Owner: bertjiazheng
- License: mit
- Created: 2022-06-11T09:58:02.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-11-25T07:56:51.000Z (26 days ago)
- Last Synced: 2024-11-25T08:45:11.137Z (26 days ago)
- Topics: awesome, cad, computer-vision, deep-learning
- Homepage:
- Size: 73.2 KB
- Stars: 142
- Watchers: 17
- Forks: 24
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- ultimate-awesome - awesome-CAD - 😎 A list of awesome Computer-Aided Design (CAD) papers. (Other Lists / Monkey C Lists)
README
# Awesome CAD [](https://github.com/sindresorhus/awesome)
A curated list of awesome Computer-Aided Design (CAD) papers, inspired by [awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision).
## Datasets
| Papers | Venue | Links |
|--------|-------|-------|
| [CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representations](https://arxiv.org/abs/2208.10555) | 3DV 2022 | [[project](https://cvi2.uni.lu/cc3d-ops/)] |
| [Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Construction from Human Design Sequences](https://arxiv.org/abs/2010.02392) | SIGGRAPH 2021 | [[project](https://github.com/AutodeskAILab/Fusion360GalleryDataset)] |
| [AutoMate: A Dataset and Learning Approach for Automatic Mating of CAD Assemblies](https://arxiv.org/abs/2105.12238) | SIGGRAPH Asia 2021 | [[project](https://github.com/deGravity/automate)] |
| [PVDeconv: Point-voxel deconvolution for autoencoding cad construction in 3D](https://arxiv.org/abs/2101.04493) | ICIP 2020 | [[project](https://cvi2.uni.lu/cc3d-dataset/)] |
| [SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design](https://arxiv.org/abs/2007.08506) | ICML Workshop 2020 | [[project]](https://github.com/PrincetonLIPS/SketchGraphs) |
| [A Large-scale Annotated Mechanical Components Benchmark for Classification and Retrieval Tasks with Deep Neural Networks (MCB)](https://www.cs.utexas.edu/~huangqx/mcb_benchmark.pdf) | ECCV 2020 | [[project](https://engineering.purdue.edu/cdesign/wp/a-large-scale-annotated-mechanical-components-benchmark-for-classification-and-retrieval-tasks-with-deep-neural-networks/)] |
| [ABC: A Big CAD Model Dataset For Geometric Deep Learning](https://arxiv.org/abs/1812.06216) | CVPR 2019 | [[project](https://deep-geometry.github.io/abc-dataset/)] |
## CAD Reconstruction
| Papers | Venue | Links |
|--------|-------|-------|
| [PlankAssembly: Robust 3D Reconstruction from Three Orthographic Views with Learnt Shape Programs](https://arxiv.org/abs/2308.05744) | ICCV 2023 | [[project](https://manycore-research.github.io/PlankAssembly/)] [[code](https://github.com/manycore-research/PlankAssembly/)] |
| [SolidGen: An Autoregressive Model for Direct B-rep Synthesis](https://arxiv.org/abs/2203.13944) | TMLR 2023 | |
| [Reconstructing Editable Prismatic CAD from Rounded Voxel Models](https://arxiv.org/abs/2209.01161) | SIGGRAPH Asia 2022 | |
| [ComplexGen: CAD Reconstruction by B-Rep Chain Complex Generation](https://arxiv.org/abs/2205.14573) | SIGGRAPH 2022 | [[project](https://haopan.github.io/complexgen.html)] [[code](https://github.com/guohaoxiang/ComplexGen)] |
| [Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinders](https://arxiv.org/abs/2112.09329) | CVPR 2022 | [[project](https://point2cyl.github.io/)] [[code](https://github.com/mikacuy/point2cyl)] |
| [PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds](https://arxiv.org/abs/2103.02766) | ICLR 2021 | [[code](https://github.com/YujiaLiu76/PC2WF)] |
| [PIE-NET: Parametric Inference of Point Cloud Edges](https://arxiv.org/abs/2007.04883) | NeurIPS 2020 | [[code](https://github.com/wangxiaogang866/PIE-NET)] |
| [ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds](https://arxiv.org/abs/2003.12181) | ECCV 2020 | [[project](https://hippogriff.github.io/parsenet/)] [[code](https://github.com/Hippogriff/parsenet-codebase)] |
| [Supervised Fitting of Geometric Primitives to 3D Point Clouds](https://arxiv.org/abs/1811.08988) | CVPR 2019 | [[code](https://github.com/lingxiaoli94/SPFN)] |
## CAD Generation
| Papers | Venue | Links |
|--------|-------|-------|
| [Text2CAD: Text to 3D CAD Generation via Technical Drawings](https://arxiv.org/abs/2411.06206) | NeurIPS 2024 | [[project](https://sadilkhan.github.io/text2cad-project/)] |
| [FlexCAD: Unified and Versatile Controllable CAD Generation with Fine-tuned Large Language Models](https://arxiv.org/abs/2411.05823) | CoRR 2024 | |
| [CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketches](https://arxiv.org/abs/2409.17457) | NeurIPS Workshop 2024 | |
| [BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry](https://arxiv.org/abs/2401.15563) | SIGGRAPH 2024 | [[code](https://github.com/samxuxiang/BrepGen)] |
| [3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows](https://arxiv.org/abs/2210.11603)| CoRR 2022 | |
| Free2CAD: Parsing Freehand Drawings into CAD Commands | SIGGRAPH 2022 | [[project](https://geometry.cs.ucl.ac.uk/projects/2022/free2cad/)] [[code](https://github.com/Enigma-li/Free2CAD)] |
| [SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks](https://arxiv.org/abs/2207.04632) | ICML 2022 | [[project](https://samxuxiang.github.io/skexgen)] [[code](https://github.com/samxuxiang/SkexGen)] |
| [Vitruvion: A Generative Model of Parametric CAD Sketches](https://arxiv.org/abs/2109.14124) | ICLR 2022 | [[project]](https://lips.cs.princeton.edu/vitruvion/) [[code](https://github.com/PrincetonLIPS/vitruvion)] |
| [JoinABLe: Learning Bottom-up Assembly of Parametric CAD Joints](https://arxiv.org/abs/2111.12772) | CVPR 2022 | [[code](https://github.com/AutodeskAILab/JoinABLe)] |
| [SketchGen: Generating Constrained CAD Sketches](https://arxiv.org/abs/2106.02711) | NeurIPS 2021 | |
| [Computer-Aided Design as Language](https://arxiv.org/abs/2105.02769) | NeurIPS 2021 | [[data](http://github.com/deepmind/deepmind-research/blob/master/cadl)] |
| [DeepCAD: A Deep Generative Network for Computer-Aided Design Models](https://arxiv.org/abs/2105.09492) | ICCV 2021 | [[project](http://www.cs.columbia.edu/cg/deepcad/)] [[code](https://github.com/ChrisWu1997/DeepCAD)] |
| [Engineering Sketch Generation for Computer-Aided Design](https://arxiv.org/abs/2104.09621) | CVPR Workshop 2021 | |
| [Sketch2CAD: Sequential CAD Modeling by Sketching in Context](https://arxiv.org/abs/2009.04927) | SIGGRAPH Asia 2020 | [[project](http://geometry.cs.ucl.ac.uk/projects/2020/sketch2cad/)] [[code](https://github.com/Enigma-li/Sketch2CAD)] |
| [PolyGen: An Autoregressive Generative Model of 3D Meshes](https://arxiv.org/abs/2002.10880) | ICML 2020 | [[code](https://github.com/deepmind/deepmind-research/blob/master/polygen/)] |
## CAD Representation
| Papers | Venue | Links |
|--------|-------|-------|
| [DualCSG: Learning Dual CSG Trees for General and Compact CAD Modeling](https://arxiv.org/abs/2301.11497) | CoRR 2023 | |
| [Discovering Design Concepts for CAD Sketches](https://arxiv.org/abs/2210.14451) | NeurIPS 2022 | [[code](https://github.com/yyuezhi/SketchConcept)] |
| [Self-Supervised Representation Learning for CAD](https://arxiv.org/abs/2210.10807) | CVPR 2023 | |
| [CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representations](https://arxiv.org/abs/2208.10555) | 3DV 2022 | |
| [CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing](https://arxiv.org/abs/2108.11305) | ICCV 2021 | [[code](https://github.com/kimren227/CSGStumpNet)] |
| [UV-Net: Learning from Boundary Representations](https://arxiv.org/abs/2006.10211) | CVPR 2021 | [[code](https://github.com/AutodeskAILab/UV-Net)] |
| [BRepNet: A Topological Message Passing System for Solid Models](https://arxiv.org/abs/2104.00706) | CVPR 2021 | [[code](https://github.com/AutodeskAILab/BRepNet)] |
| [CSGNet: Neural Shape Parser for Constructive Solid Geometry](https://arxiv.org/abs/1712.08290) | CVPR 2018 | [[code](https://github.com/Hippogriff/CSGNet)] |
## CAD Recognition
| Papers | Venue | Links |
|--------|-------|-------|
| [Symbol as Points: Panoptic Symbol Spotting via Point-based Representation](https://arxiv.org/abs/2401.10556) | ICLR 2024 | [[code](https://github.com/nicehuster/SymPoint)] |
| [VectorFloorSeg: Two-Stream Graph Attention Network for Vectorized Roughcast Floorplan Segmentation](https://openaccess.thecvf.com/content/CVPR2023/html/Yang_VectorFloorSeg_Two-Stream_Graph_Attention_Network_for_Vectorized_Roughcast_Floorplan_Segmentation_CVPR_2023_paper.html) | CVPR 2023 | [[code](https://github.com/DrZiji/VecFloorSeg)] |
| [CADTransformer: Panoptic Symbol Spotting Transformer for CAD Drawings](https://openaccess.thecvf.com/content/CVPR2022/papers/Fan_CADTransformer_Panoptic_Symbol_Spotting_Transformer_for_CAD_Drawings_CVPR_2022_paper.pdf)| CVPR 2022 | [[code](https://github.com/VITA-Group/CADTransformer)] |
| [GAT-CADNet: Graph Attention Network for Panoptic Symbol Spotting in CAD Drawings](https://arxiv.org/abs/2201.00625) | CVPR 2022 | |
| [FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol Spotting](https://arxiv.org/abs/2105.07147) | ICCV 2021 | [[project](https://floorplancad.github.io/)] |