WEAKLY SUPERVISED SEGMENTATION-AIDED CLASSIFICATION OF URBAN SCENES FROM 3D LIDAR POINT CLOUDS

46 citations as recorded by crossref.

1. Toward Building and Civil Infrastructure Reconstruction From Point Clouds: A Review on Data and Key Techniques Y. Xu & U. Stilla
2. An Automatic Method for Tree Species Point Cloud Segmentation Based on Deep Learning L. Pu et al.
3. Automatic Extraction and Labelling of Memorial Objects From 3D Point Clouds N. Arnold et al.
4. Weld Bead Detection Based on 3D Geometric Features and Machine Learning Approaches P. Rodriguez-Gonzalvez & M. Rodriguez-Martin
5. 基于车载激光点云的路面坑槽检测方法 马. Ma Xinjiang et al.
6. LeWoS: A universal leaf‐wood classification method to facilitate the 3D modelling of large tropical trees using terrestrial LiDAR D. Wang et al.
7. E-L 0: Advanced Surface Segmentation of LiDAR Point Clouds in Open-Pit Mine Stepped Terrain T. Chen et al.
8. Hierarchical heterogeneous graph learning for color-missing ALS pointcloud segmentation B. Huang & Y. Zhu
9. The 3D narrow butt weld seam detection system based on the binocular consistency correction X. Wang et al.
10. A Convolutional Neural Network-Based 3D Semantic Labeling Method for ALS Point Clouds Z. Yang et al.
11. FAIS: Fully Automatic Indoor Surveying Framework of Terrestrial Laser Scanning Point Clouds in Large-Scale Indoor Environments W. Li et al.
12. DCARN: Deep Context Aware Recurrent Neural Network for Semantic Segmentation of Large Scale Unstructured 3D Point Cloud S. Mehmood et al.
13. Local-to-global structure prior guided high-precision point cloud registration framework based on FPP X. Wang et al.
14. Segmentation and Multi-Scale Convolutional Neural Network-Based Classification of Airborne Laser Scanner Data Z. Yang et al.
15. Geospatial Computer Vision Based on Multi-Modal Data—How Valuable Is Shape Information for the Extraction of Semantic Information? M. Weinmann & M. Weinmann
16. Weakly-Supervised Point Cloud Segmentation Combining Pseudo Label Generation and Noise Label Learning A. Deng et al.
17. Weakly supervised semantic segmentation of airborne laser scanning point clouds Y. Lin et al.
18. Comparison of stand characteristic parameters and biomass estimations from light detection and ranging and structure-from-motion point clouds Z. Xu et al.
19. Region-Based Edge Convolutions With Geometric Attributes for the Semantic Segmentation of Large-Scale 3-D Point Clouds J. Contreras et al.
20. Road boundary extraction method from mobile laser scanning point clouds G. Xin et al.
21. 3D point cloud descriptors: state-of-the-art X. Han et al.
22. A new weakly supervised approach for ALS point cloud semantic segmentation P. Wang & W. Yao
23. Mesh Oversegmentation with Segmentation-Aware Loss J. Adam et al.
24. Mapping multispectral Digital Images using a Cloud Computing software: applications from UAV images J. Saura et al.
25. Sparse and Low-Overlapping Point Cloud Registration Network for Indoor Building Environments Z. Zhang et al.
26. Pseudo-labelling-aided semantic segmentation on sparsely annotated 3D point clouds Y. Yao et al.
27. Region-Enhanced Feature Learning for Scene Semantic Segmentation X. Kang et al.
28. Integrating OpenStreetMap tags for efficient LiDAR point cloud classification using graph neural networks Y. Chen et al.
29. Multispectral point cloud superpoint segmentation Q. Wang et al.
30. Road Segmentation and Environment Labeling for Autonomous Vehicles R. Chen et al.
31. Classification of LiDAR Point Clouds Using Supervoxel-Based Detrended Feature and Perception-Weighted Graphical Model Y. Xu et al.
32. Dynamic Scene Graph Generation of Point Clouds with Structural Representation Learning C. Qi et al.
33. GECNN for Weakly Supervised Semantic Segmentation of 3D Point Clouds Z. HE et al.
34. Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling T. Arevalo-Ramirez & F. Auat Cheein
35. LiDAR remote sensing meets weak supervision: Concepts, methods, and perspectives Y. Gao et al.
36. Supervised Contrastive Learning for Indoor Point Cloud Oversegmentation Y. Sun et al.
37. A Deep Learning-Based Method for Extracting Standing Wood Feature Parameters from Terrestrial Laser Scanning Point Clouds of Artificially Planted Forest X. Shen et al.
38. Multigranularity Semantic Labeling of Point Clouds for the Measurement of the Rail Tanker Component With Structure Modeling C. Qi & J. Yin
39. Segmentation of Individual Trees in TLS Point Clouds via Graph Optimization Y. Liu et al.
40. A structured regularization framework for spatially smoothing semantic labelings of 3D point clouds L. Landrieu et al.
41. Using Training Samples Retrieved from a Topographic Map and Unsupervised Segmentation for the Classification of Airborne Laser Scanning Data Z. Yang et al.
42. A note on the forward-Douglas–Rachford splitting for monotone inclusion and convex optimization H. Raguet
43. 3DGraphSeg: A Unified Graph Representation- Based Point Cloud Segmentation Framework for Full-Range High-Speed Railway Environments Y. Geng et al.
44. Point Cloud Semantic Segmentation by Adaptively Fusing Information With Varying Distances Z. Jiang et al.
45. Road potholes detection from MLS point clouds X. Ma et al.
46. GrowSP++: Growing Superpoints and Primitives for Unsupervised 3D Semantic Segmentation Z. Zhang et al.