mlsanityData to 14 Oct 2026

Parametric Point Cloud Completion for Polygonal Surface Reconstruction

arXiv 2503.08363 ↗First posted 11 Mar 2025cs.CVcited by 6

Not on the map. Why?

Abstract (arXiv)

Existing polygonal surface reconstruction methods heavily depend on input completeness and struggle with incomplete point clouds. We argue that while current point cloud completion techniques may recover missing points, they are not optimized for polygonal surface reconstruction, where the parametric representation of underlying surfaces remains overlooked. To address this gap, we introduce parametric completion, a novel paradigm for point cloud completion, which recovers parametric primitives instead of individual points to convey high-level geometric structures. Our presented approach, PaCo, enables high-quality polygonal surface reconstruction by leveraging plane proxies that encapsulate both plane parameters and inlier points, proving particularly effective in challenging scenarios with highly incomplete data. Comprehensive evaluations of our approach on the ABC dataset establish its effectiveness with superior performance and set a new standard for polygonal surface reconstruction from incomplete data. Project page: https://parametric-completion.github.io.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 31 of its 54 references that are in the map. First posted on arXiv 11 Mar 2025.

Builds on

31 of 54 references.

References · 31

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020End-to-End Object Detection with Transformerscited by 7,414
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  4. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  5. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,223
  6. 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,205
  7. 2018PCN: Point Completion Networkcited by 384
  8. 2018ABC: A Big CAD Model Dataset For Geometric Deep Learningcited by 341
  9. 2021PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformerscited by 286
  10. 2016Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesiscited by 219
  11. 2018PU-Net: Point Cloud Upsampling Networkcited by 209
  12. 2019BSP-Net: Generating Compact Meshes via Binary Space Partitioningcited by 206
19 more
  1. 2020GRNet: Gridding Residual Network for Dense Point Cloud Completioncited by 174
  2. 2021SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformercited by 164
  3. 2020Points2Surf: Learning Implicit Surfaces from Point Cloud Patchescited by 122
  4. 2023Neural Kernel Surface Reconstructioncited by 104
  5. 2022POCO: Point Convolution for Surface Reconstructioncited by 92
  6. 2022SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformercited by 83
  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
  9. 2023SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operationscited by 46
  10. 2023ProxyFormer: Proxy Alignment Assisted Point Cloud Completion with Missing Part Sensitive Transformercited by 43
  11. 2022Surface Reconstruction from Point Clouds: A Survey and a Benchmarkcited by 41
  12. 2023Point2CAD: Reverse Engineering CAD Models from 3D Point Cloudscited by 36
  13. 2022LAKe-Net: Topology-Aware Point Cloud Completion by Localizing Aligned Keypointscited by 27
  14. 2022City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Cloudscited by 22
  15. 2022CSDN: Cross-modal Shape-transfer Dual-refinement Network for Point Cloud Completioncited by 22
  16. 2021Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fieldscited by 20
  17. 2022FBNet: Feedback Network for Point Cloud Completioncited by 20
  18. 2023PolyGNN: Polyhedron-based Graph Neural Network for 3D Building Reconstruction from Point Cloudscited by 10
  19. 2024Concise Plane Arrangements for Low-Poly Surface and Volume Modellingcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 4.

6 papers.

  1. 2025Learning Generalizable Shape Completion with SIM(3) Equivariancecited by 2
  2. 2026MGPC: Multimodal Network for Generalizable Point Cloud Completion With Modality Dropout and Progressive Decodingcited by 2
  3. 2025HeartFormer: Semantic-Aware Dual-Structure Transformers for 3D Four-Chamber Cardiac Point Cloud Reconstructioncited by 1
  4. 2026BuildAnyPoint: 3D Building Structured Abstraction from Diverse Point Cloudscited by 1
  5. 2026Unified Primitive Proxies for Structured Shape Completioncited by 0
  6. 2026Confidence-Driven Facade Refinement of 3D Building Models Using MLS Point Cloudscited by 0