Awesome Planar Reconstruction 
Papers
Those with piece-wise planarity are highlighted.
Plane Extraction / Detection
| Title |
Authors |
Venue |
Year |
Resources |
| Efficient RANSAC for Point-Cloud Shape Detection |
Ruwen Schnabel et al. |
Computer Graphics Forum |
2007 |
[PDF] [CODE] |
| The 3D Hough Transform for Plane Detection in Point Clouds: A Review and a new Accumulator Design |
Dorit Borrmann et al. |
3D Research |
2011 |
[PDF] |
| Planar Shape Detection at Structural Scales |
Hao Fang et al. |
CVPR |
2018 |
[PDF] |
| Plane Segmentation Based on the Optimal-vector-field in LiDAR Point Clouds |
Sheng Xu et al. |
PAMI |
2020 |
[PDF] |
| From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds |
Christiane Sommer et al. |
ICRA |
2020 |
[PDF] [CODE] |
| Supervised Fitting of Geometric Primitives to 3D Point Clouds |
Lingxiao Li et al. |
CVPR |
2019 |
[PDF] [CODE] |
| Highly Parallelizable Plane Extraction for Organized Point Clouds Using Spherical Convex Hulls |
Hannes Möls et al. |
ICRA |
2020 |
[PDF] |
| CPFN: Cascaded Primitive Fitting Networks for High-Resolution Point Clouds |
Eric-Tuan Lê et al. |
ICCV |
2021 |
[PDF] [CODE] |
Single-view Reconstruction
| Title |
Authors |
Venue |
Year |
Resources |
| PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image |
Chen Liu et al. |
CVPR |
2018 |
[PDF] [CODE] |
| Recovering 3D Planes from a Single Image via Convolutional Neural Networks |
Fengting Yang and Zihan Zhou |
ECCV |
2018 |
[PDF] [CODE] |
| PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image |
Chen Liu et al. |
CVPR |
2019 |
[PDF] [CODE] |
| Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding |
Zehao Yu et al. |
CVPR |
2019 |
[PDF] [CODE] |
| Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks |
Junyi Pan et al. |
ICCV |
2019 |
[PDF] [CODE] |
| Mesh R-CNN |
Georgia Gkioxari et al. |
ICCV |
2019 |
[PDF] [CODE] |
| Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction |
Yiming Qian and Yasutaka Furukawa |
ECCV |
2020 |
[PDF] |
Multi-view Reconstruction
| Title |
Authors |
Venue |
Year |
Resources |
| Reconstructing piecewise planar scenes with multi-view regularization |
Weijie Xi and Xuejin Chen |
Computational Visual Media |
2019 |
[PDF] |
| PlaneMVS: 3D Plane Reconstruction from Multi-View Stereo |
Jiachen Liu et al. |
CVPR |
2022 |
[PDF] |
Generative / Implicit Field
| Title |
Authors |
Venue |
Year |
Resources |
| Continuous Signed Distance Functions for 3D Vision |
Simen Haugo et al. |
3DV |
2017 |
[PDF] |
| AtlasNet: A Papier-Mâché Approach to Learning 3D Surface |
Thibault Groueix et al. |
CVPR |
2018 |
[PDF] [CODE] |
| DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation |
Jeong Joon Park et al. |
CVPR |
2019 |
[PDF] [CODE] |
| Occupancy Networks: Learning 3D Reconstruction in Function Space |
Lars Mescheder et al. |
CVPR |
2019 |
[PDF] [CODE] |
| Learning Implicit Fields for Generative Shape Modeling |
Zhiqin Chen and Hao Zhang |
CVPR |
2019 |
[PDF] [CODE] |
| Learning Shape Templates with Structured Implicit Functions |
Kyle Genova et al. |
ICCV |
2019 |
[PDF] |
| BSP-Net: Generating Compact Meshes via Binary Space Partitioning |
Zhiqin Chen et al. |
CVPR |
2020 |
[PDF] [CODE] |
| Points2Surf: Learning Implicit Surfaces from Point Clouds |
Philipp Erler et al. |
ECCV |
2020 |
[PDF] [CODE] |
| Overfit Neural Networks as a Compact Shape Representation |
Thomas Davies et al. |
arXiv |
2020 |
[PDF] |
| Implicit Geometric Regularization for Learning Shapes |
Amos Gropp et al. |
ICML |
2020 |
[PDF] [CODE] |
| Deep Parametric Shape Predictions using Distance Fields |
Dmitriy Smirnov et al. |
CVPR |
2020 |
[PDF] [CODE] |
| PolyGen: An Autoregressive Generative Model of 3D Meshes |
Charlie Nash et al. |
arXiv |
2020 |
[PDF] |
| CvxNet: Learnable Convex Decomposition |
Boyang Deng et al. |
arXiv |
2020 |
[PDF] [CODE] |
| Local Deep Implicit Functions for 3D Shape |
Kyle Genova et al. |
CVPR |
2020 |
[PDF] [CODE] |
| Coupling Explicit and Implicit Surface Representations for Generative 3D Modeling |
Omid Poursaeed et al. |
ECCV |
2020 |
[PDF] |
| CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assembly |
Fenggen Yu et al. |
CVPR |
2022 |
[PDF] |
| Neural 3D Scene Reconstruction with the Manhattan-world Assumption |
Haoyu Guo et al. |
CVPR |
2022 |
[PAGE] |
| NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priors |
Jiepeng Wang et al. |
ECCV |
2022 |
[PAGE] |
Kinetic Reconstruction
| Title |
Authors |
Venue |
Year |
Resources |
| KIPPI: KInetic Polygonal Partitioning of Images |
JEAN-PHILIPPE BAUCHET and FLORENT LAFARGE |
CVPR |
2018 |
[PDF] [CODE] |
| Approximating shapes in images with low-complexity polygons |
Muxingzi Li et al. |
CVPR |
2020 |
[PDF] [CODE] |
| Kinetic Shape Reconstruction |
JEAN-PHILIPPE BAUCHET and FLORENT LAFARGE |
SIGGRAPH |
2020 |
[PDF] |
Mesh Deformation
| Title |
Authors |
Venue |
Year |
Resources |
| Point2Mesh: A Self-Prior for Deformable Meshes |
RANA HANOCKA et al. |
SIGGRAPH |
2020 |
[PDF] [CODE] |
| ShapeFlow: Learnable Deformations Among 3D Shapes |
Chiyu Jiang et al. |
NeurIPS |
2020 |
[PDF] [CODE] |
| Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic Flows |
Kunal Gupta and Manmohan Chandraker |
NeurIPS |
2020 |
[PDF] [CODE] |
| Learning Deformable Tetrahedral Meshes for 3D Reconstruction |
Jun Gao et al. |
NeurIPS |
2020 |
[PDF] [CODE] |
Constructive / Parametric Geometry
| Title |
Authors |
Venue |
Year |
Resources |
| Boolean operations on 3D selective Nef complexes: Data structure, algorithms, optimized implementation and experiments |
Peter Hachenberger et al. |
Computational Geometry |
2007 |
[PDF] [CODE] |
| Mesh arrangements for solid geometry |
Qingnan Zhou et al. |
SIGGRAPH |
2016 |
[PDF] [CODE] |
| 3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks |
Chuhang Zou et al. |
ICCV |
2017 |
[PDF] [CODE] |
| CSGNet: Neural Shape Parser for Constructive Solid Geometry |
Gopal Sharma et al. |
CVPR |
2018 |
[PDF] |
| Surface Reconstruction from 3D Line Segments |
Pierre-Alain Langlois et al. |
3DV |
2019 |
[PDF] [CODE] |
| ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds |
Gopal Sharma et al. |
ECCV |
2020 |
[PDF] [CODE] |
| PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes arXiv:1911.10949v3 |
Rundi Wu et al. |
CVPR |
2020 |
[PDF] [CODE] |
| UCSG-Net -- Unsupervised Discovering of Constructive Solid Geometry Tree |
Kacper Kania et al. |
NIPS |
2020 |
[PDF] [CODE] |
| State of the Art on Computational Design of Assemblies with Rigid Parts |
Ziqi Wang et al. |
EUROGRAPHICS |
2021 |
[PDF] |
| Reconstruction of Convex Polytope Compositions from 3D Point-clouds |
Markus Friedrich and Pierre-Alain Fayolle |
GRAPP |
2021 |
[PDF] [CODE] |
Triangulation
| Title |
Authors |
Venue |
Year |
Resources |
| PointTriNet: Learned Triangulation of 3D Point Sets |
Nicholas Sharp and Maks Ovsjanikov |
ECCV |
2020 |
[PDF] [CODE] |
Wireframe
| Title |
Authors |
Venue |
Year |
Resources |
| PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds |
Yujia Liu et al. |
ICLR |
2021 |
[PDF] |
Urban Reconstruction
| Title |
Authors |
Venue |
Year |
Resources |
| LOD Generation for Urban Scenes |
Yannick Verdie et al. |
ACM TOG |
2015 |
[PDF] |
| Manhattan-world Urban Reconstruction from Point Clouds |
Minglei Li et al. |
ECCV |
2016 |
[PDF] |
| Connect-and-Slice: an hybrid approach for reconstructing 3D objects |
Hao Fang et al. |
CVPR |
2020 |
[PDF] |
| Relation-Constrained Automatic 3D Reconstruction of Buildings in Metropolitan Areas from Photogrammetric Point Clouds |
Yuan Li and Bo Wu |
Remote Sensing |
2021 |
[PDF] |
| Combined Rule-Based and Hypothesis-Based Method for Building Model Reconstruction from Photogrammetric Point Clouds |
Linfu Xie et al. |
Remote Sensing |
2021 |
[PDF] |
| Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields |
Zhaiyu Chen et al. |
ISPRS |
2022 |
[PDF] [CODE] |
| Point2Roof: End-to-end 3D Building Roof Modeling from Airborne LiDAR Point Clouds |
Li Li et al. |
ISPRS |
2022 |
[PDF] [CODE] |
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
