FAST SEMANTIC SEGMENTATION OF 3D POINT CLOUDS WITH STRONGLY VARYING DENSITY

99 citations as recorded by crossref.

1. Geospatial Computer Vision Based on Multi-Modal Data—How Valuable Is Shape Information for the Extraction of Semantic Information? M. Weinmann & M. Weinmann 10.3390/rs10010002
2. Machine Learning and Deep Learning for the Built Heritage Analysis: Laser Scanning and UAV-Based Surveying Applications on a Complex Spatial Grid Structure D. Billi et al. 10.3390/rs15081961
3. Comparison of Different Feature Sets for TLS Point Cloud Classification Q. Li & X. Cheng 10.3390/s18124206
4. An Object-Based Bidirectional Method for Integrated Building Extraction and Change Detection between Multimodal Point Clouds C. Dai et al. 10.3390/rs12101680
5. Supervised Classification of Power Lines from Airborne LiDAR Data in Urban Areas Y. Wang et al. 10.3390/rs9080771
6. Deep Learning on Point Clouds and Its Application: A Survey W. Liu et al. 10.3390/s19194188
7. DCNet: Large-Scale Point Cloud Semantic Segmentation With Discriminative and Efficient Feature Aggregation F. Yin et al. 10.1109/TCSVT.2023.3239541
8. A Convolutional Neural Network-Based 3D Semantic Labeling Method for ALS Point Clouds Z. Yang et al. 10.3390/rs9090936
9. An encoder-decoder deep learning method for multi-class object segmentation from 3D tunnel point clouds A. Ji et al. 10.1016/j.autcon.2022.104187
10. T-LOAM: Truncated Least Squares LiDAR-Only Odometry and Mapping in Real Time P. Zhou et al. 10.1109/TGRS.2021.3083606
11. 3D Point Cloud Semantic Segmentation Through Functional Data Analysis M. Oviedo de la Fuente et al. 10.1007/s13253-023-00567-w
12. GSIP: Green Semantic Segmentation of Large-Scale Indoor Point Clouds M. Zhang et al. 10.1016/j.patrec.2022.10.014
13. Geometric characterization and segmentation of historic buildings using classification algorithms and convolutional networks in HBIM J. Moyano et al. 10.1016/j.autcon.2024.105728
14. Evaluation of LiDAR-Derived Features Relevance and Training Data Minimization for 3D Point Cloud Classification S. Morsy & A. Shaker 10.3390/rs14235934
15. Multilevel intuitive attention neural network for airborne LiDAR point cloud semantic segmentation Z. Wang et al. 10.1016/j.jag.2024.104020
16. An Efficient Framework for Mobile Lidar Trajectory Reconstruction and Mo-norvana Segmentation E. Che & M. Olsen 10.3390/rs11070836
17. Classification of Tree Species as Well as Standing Dead Trees Using Triple Wavelength ALS in a Temperate Forest N. Amiri et al. 10.3390/rs11222614
18. Integrate Point-Cloud Segmentation with 3D LiDAR Scan-Matching for Mobile Robot Localization and Mapping X. Li et al. 10.3390/s20010237
19. GADA-SegNet: gated attentive domain adaptation network for semantic segmentation of LiDAR point clouds X. Kong et al. 10.1007/s00371-023-02799-w
20. A Classification-Segmentation Framework for the Detection of Individual Trees in Dense MMS Point Cloud Data Acquired in Urban Areas M. Weinmann et al. 10.3390/rs9030277
21. TUM-MLS-2016: An Annotated Mobile LiDAR Dataset of the TUM City Campus for Semantic Point Cloud Interpretation in Urban Areas J. Zhu et al. 10.3390/rs12111875
22. Machine Learning Generalisation across Different 3D Architectural Heritage E. Grilli & F. Remondino 10.3390/ijgi9060379
23. Evaluating the Quality of Semantic Segmented 3D Point Clouds E. Barnefske & H. Sternberg 10.3390/rs14030446
24. A surface graph based deep learning framework for large-scale urban mesh semantic segmentation Y. Yang et al. 10.1016/j.jag.2023.103322
25. Large-Scale ALS Data Semantic Classification Integrating Location-Context-Semantics Cues by Higher-Order CRF W. Han et al. 10.3390/s20061700
26. SUM: A benchmark dataset of Semantic Urban Meshes W. Gao et al. 10.1016/j.isprsjprs.2021.07.008
27. Precise 3D extraction of building roofs by fusion of UAV-based thermal and visible images M. Dahaghin et al. 10.1080/01431161.2021.1951875
28. Hierarchical SVM for Semantic Segmentation of 3D Point Clouds for Infrastructure Scenes M. Mansour et al. 10.3390/infrastructures9050083
29. Learning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling Q. Hu et al. 10.1109/TPAMI.2021.3083288
30. 3DMASC: Accessible, explainable 3D point clouds classification. Application to bi-spectral topo-bathymetric lidar data M. Letard et al. 10.1016/j.isprsjprs.2023.11.022
31. Approach for graph-based individual branch modelling of meadow orchard trees with 3D point clouds J. Straub et al. 10.1007/s11119-022-09964-6
32. Evaluation of data subsampling and neighbourhood selection for mobile LiDAR data classification M. Mohamed et al. 10.1016/j.ejrs.2021.04.003
33. A robust correspondence-based registration method for large-scale outdoor point cloud R. Li et al. 10.1080/17538947.2024.2407943
34. Structure-Aware Convolution for 3D Point Cloud Classification and Segmentation L. Wang et al. 10.3390/rs12040634
35. MSNet: Multi-Scale Convolutional Network for Point Cloud Classification L. Wang et al. 10.3390/rs10040612
36. Real-Time 3-D Semantic Scene Parsing With LiDAR Sensors F. Wang et al. 10.1109/TCYB.2020.2982947
37. Discrimination of Leaves in a Multi-Layered Mediterranean Forest through Machine Learning Algorithms C. Alvites et al. 10.3390/rs15184450
38. Classification of airborne 3D point clouds regarding separation of vegetation in complex environments D. Bulatov et al. 10.1364/AO.422973
39. Juggling with representations: On the information transfer between imagery, point clouds, and meshes for multi-modal semantics D. Laupheimer & N. Haala 10.1016/j.isprsjprs.2021.03.007
40. ALS Point Cloud Classification by Integrating an Improved Fully Convolutional Network into Transfer Learning with Multi-Scale and Multi-View Deep Features X. Lei et al. 10.3390/s20236969
41. Point Cloud Quality Assessment Using a One-Dimensional Model Based on the Convolutional Neural Network A. Laazoufi et al. 10.3390/jimaging10060129
42. Object Recognition, Segmentation, and Classification of Mobile Laser Scanning Point Clouds: A State of the Art Review E. Che et al. 10.3390/s19040810
43. No-Reference Quality Assessment for 3D Colored Point Cloud and Mesh Models Z. Zhang et al. 10.1109/TCSVT.2022.3186894
44. Separating Tree Photosynthetic and Non-Photosynthetic Components from Point Cloud Data Using Dynamic Segment Merging D. Wang et al. 10.3390/f9050252
45. Semantic segmentation of point cloud data using raw laser scanner measurements and deep neural networks R. Kaijaluoto et al. 10.1016/j.ophoto.2021.100011
46. 3D Classification of Cold-Water Coral Reefs: A Comparison of Classification Techniques for 3D Reconstructions of Cold-Water Coral Reefs and Seabed L. de Oliveira et al. 10.3389/fmars.2021.640713
47. VD-LAB: A view-decoupled network with local-global aggregation bridge for airborne laser scanning point cloud classification J. Li et al. 10.1016/j.isprsjprs.2022.01.012
48. Implementing PointNet for point cloud segmentation in the heritage context B. Haznedar et al. 10.1186/s40494-022-00844-w
49. Semantic Segmentation of 3D Point Clouds Based on High Precision Range Search Network Z. Su et al. 10.3390/rs14225649
50. Using Relative Projection Density for Classification of Terrestrial Laser Scanning Data with Unknown Angular Resolution M. Chen et al. 10.3390/rs14236043
51. GeoSparseNet: A Multi-Source Geometry-Aware CNN for Urban Scene Analysis M. Afzal et al. 10.3390/rs16111827
52. Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey of Datasets and Methods B. Gao et al. 10.1109/TITS.2021.3076844
53. A spatially enhanced network with camera-lidar fusion for 3D semantic segmentation C. Ye et al. 10.1016/j.neucom.2020.12.135
54. A Supervoxel-Based Random Forest Method for Robust and Effective Airborne LiDAR Point Cloud Classification L. Liao et al. 10.3390/rs14061516
55. Machine learning-based segmentation of aerial LiDAR point cloud data on building roof E. Dey et al. 10.1080/22797254.2023.2210745
56. Adaptive Multiscale Feature Extraction in a Distributed System for Semantic Classification of Airborne LiDAR Point Clouds S. Singh & J. Sreevalsan-Nair 10.1109/LGRS.2021.3099935
57. Classification of Large-Scale Mobile Laser Scanning Data in Urban Area with LightGBM E. Sevgen & S. Abdikan 10.3390/rs15153787
58. Urban 3D modeling using mobile laser scanning: a review C. Wang et al. 10.1016/j.vrih.2020.05.003
59. Adaptive neighbourhood recovery method for machine learning based 3D point cloud classification J. Xue et al. 10.1080/01431161.2022.2162354
60. A Methodological Framework for High-Resolution Surface Urban Heat Island Mapping: Integration of UAS Remote Sensing, GIS, and the Local Climate Zoning Concept S. Dimitrov et al. 10.3390/rs16214007
61. A Knowledge-Based Multi-Scale Adaptive Classification Approach for Mobile Laser Scanning Point Clouds in Urban Scenes M. Zheng et al. 10.1109/ACCESS.2023.3335607
62. An adaptive iterative reweighted filtering methodology for urban MLS dataset B. Suleymanoglu et al. 10.1080/14498596.2024.2350588
63. Point Cloud Intensity Correction for 2D LiDAR Mobile Laser Scanning X. Liu et al. 10.1155/2022/3707985
64. Overview of LiDAR point cloud target detection methods based on deep learning S. Huang et al. 10.1108/SR-01-2022-0022
65. Identification of outcropping strata from UAV oblique photogrammetric data using a spatial case-based reasoning model J. Chen et al. 10.1016/j.jag.2021.102450
66. Multi-scan segmentation of terrestrial laser scanning data based on normal variation analysis E. Che & M. Olsen 10.1016/j.isprsjprs.2018.01.019
67. Deep learning-based semantic segmentation of three-dimensional point cloud: a comprehensive review D. Singh & M. Yadav 10.1080/01431161.2023.2297177
68. Improvement of 3D LiDAR point cloud classification of urban road environment based on random forest classifier M. Mohamed et al. 10.1080/10106049.2022.2102218
69. Supervised Detection of Façade Openings in 3D Point Clouds with Thermal Attributes M. Jarząbek-Rychard et al. 10.3390/rs12030543
70. Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features M. Hillemann et al. 10.3390/rs11161955
71. BoundED: Neural boundary and edge detection in 3D point clouds via local neighborhood statistics L. Bode et al. 10.1016/j.isprsjprs.2023.09.023
72. Systematic Comparison of Power Line Classification Methods from ALS and MLS Point Cloud Data Y. Wang et al. 10.3390/rs10081222
73. Strict rule-based automatic training data extraction using Mobile laser scanning in urban area Z. Ma et al. 10.1016/j.isprsjprs.2022.10.007
74. LiDAR-Based Hatch Localization Z. Jiang et al. 10.3390/rs14205069
75. RAAFNet: Reverse Attention Adaptive Fusion Network for Large-Scale Point Cloud Semantic Segmentation K. Wang & H. Zhang 10.3390/math12162485
76. Combined Edge- and Stixel-based Object Detection in 3D Point Cloud F. Hu et al. 10.3390/s19204423
77. Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review S. Yang et al. 10.3390/rs15030548
78. Hybrid 3D Reconstruction of Indoor Scenes Integrating Object Recognition M. Li et al. 10.3390/rs16040638
79. Evaluation of Machine Learning Algorithms for Classification of Infrastructure Elements in Complex Structures Y. Yilmaz et al. 10.1007/s12205-024-2062-8
80. Traffic Sign Three‐Dimensional Reconstruction Based on Point Clouds and Panoramic Images M. Wang et al. 10.1111/phor.12398
81. Vehicle specific robust traversability indices using roadmaps on 3D pointclouds M. Khan et al. 10.1007/s41315-020-00148-x
82. Recent Advances and Perspectives in Deep Learning Techniques for 3D Point Cloud Data Processing Z. Ding et al. 10.3390/robotics12040100
83. Pole-Like Road Furniture Detection and Decomposition in Mobile Laser Scanning Data Based on Spatial Relations F. Li et al. 10.3390/rs10040531
84. An Efficient and General Framework for Aerial Point Cloud Classification in Urban Scenarios E. Özdemir et al. 10.3390/rs13101985
85. An Inverse Node Graph-Based Method for the Urban Scene Segmentation of 3D Point Clouds B. Zhao et al. 10.3390/rs13153021
86. PSSNet: Planarity-sensible Semantic Segmentation of large-scale urban meshes W. GAO et al. 10.1016/j.isprsjprs.2022.12.020
87. Automating Parameter Learning for Classifying Terrestrial LiDAR Point Cloud Using 2D Land Cover Maps C. Feng & Z. Guo 10.3390/rs10081192
88. Semantic segmentation of surface from lidar point cloud A. Mukherjee et al. 10.1007/s11042-020-09841-2
89. Classification of 3D Digital Heritage E. Grilli & F. Remondino 10.3390/rs11070847
90. Deep Learning-Based Semantic Segmentation of Urban Features in Satellite Images: A Review and Meta-Analysis B. Neupane et al. 10.3390/rs13040808
91. Stem Detection from Terrestrial Laser Scanning Data with Features Selected via Stem-Based Evaluation M. Chen et al. 10.3390/f14102035
92. Advanced Semi-Automatic Approach for Identifying Damaged Surfaces in Cultural Heritage Sites: Integrating UAVs, Photogrammetry, and 3D Data Analysis T. Caciora et al. 10.3390/rs16163061
93. Classification of Coastal Benthic Substrates Using Supervised and Unsupervised Machine Learning Models on North Shore of the St. Lawrence Maritime Estuary (Canada) G. Labbé-Morissette et al. 10.3390/geomatics4030013
94. Pavement distress detection using terrestrial laser scanning point clouds – Accuracy evaluation and algorithm comparison Z. Feng et al. 10.1016/j.ophoto.2021.100010
95. Building semantic segmentation from large-scale point clouds via primitive recognition C. Romanengo et al. 10.1016/j.gmod.2024.101234
96. FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation A. Xiao et al. 10.1016/j.isprsjprs.2021.04.011
97. Semantic segmentation of large-scale point clouds based on dilated nearest neighbors graph L. Wang et al. 10.1007/s40747-021-00618-0
98. Modelling spatio-temporal ageing phenomena with deep Generative Adversarial Networks S. Papadopoulos et al. 10.1016/j.image.2021.116200
99. SPS-LCNN: A Significant Point Sampling-based Lightweight Convolutional Neural Network for point cloud processing H. Xu & J. Bai 10.1016/j.asoc.2023.110498