A REVIEW OF POINT CLOUDS SEGMENTATION AND CLASSIFICATION ALGORITHMS

202 citations as recorded by crossref.

1. Advancements in 3D Heritage Data Aggregation and Enrichment in Europe: Implications for Designing the Jena Experimental Repository for the DFG 3D Viewer S. Münster https://doi.org/10.3390/app13179781
2. Deep Learning–Based Automated Generation of Material Data with Object–Space Relationships for Scan to BIM S. Kim et al. https://doi.org/10.1061/JMENEA.MEENG-5143
3. Indoor Point Cloud Segmentation Using a Modified Region Growing Algorithm and Accurate Normal Estimation W. Wang et al. https://doi.org/10.1109/ACCESS.2023.3270709
4. Integration of Laser Scanning, Digital Photogrammetry and BIM Technology: A Review and Case Studies A. Borkowski & A. Kubrat https://doi.org/10.3390/eng5040125
5. Asymmetrical siamese network for point clouds normal estimation W. Jin et al. https://doi.org/10.1016/j.eswa.2025.127401
6. Point cloud segmentation method based on an image mask and its application verification J. Cao et al. https://doi.org/10.1088/1361-6501/ad89e5
7. Building Footprint Extraction from Classified TLS Point Clouds: Evaluation of Point Cloud Cleaning Methods P. Peťovský et al. https://doi.org/10.3390/geomatics6030056
8. Point Cloud Segmentation from iPhone-Based LiDAR Sensors Using the Tensor Feature X. Wang et al. https://doi.org/10.3390/app12041817
9. Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment M. Aslani & S. Seipel https://doi.org/10.1016/j.apenergy.2021.118033
10. Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method K. Shibano et al. https://doi.org/10.1007/s10333-023-00965-3
11. Automated Steel Structure Model Reconstruction through Point Cloud Instance Segmentation and Parametric Shape Fitting F. Noichl et al. https://doi.org/10.36680/j.itcon.2025.045
12. High-precision repairing algorithm research for core point cloud holes based on boundary feature free-form surface Y. Ding et al. https://doi.org/10.1080/10916466.2025.2588186
13. Global frequency-aware multi-scale feature learning for point cloud normal estimation W. Jin et al. https://doi.org/10.1016/j.engappai.2025.113227
14. Geometric-Feature-Enhanced Deep Learning for Bridge Point Cloud Segmentation under LiDAR Occlusion J. Han et al. https://doi.org/10.1061/JCCEE5.CPENG-7632
15. Two-Dimensional Shape Analysis of Complex Geometry Based on Photogrammetric Models of Iconostases I. Đurić et al. https://doi.org/10.3390/app11157042
16. 3D Point Cloud for Cultural Heritage: A Scientometric Survey S. Yang et al. https://doi.org/10.3390/rs14215542
17. Comparative Analysis of Algorithms to Cleanse Soil Micro-Relief Point Clouds S. Ott et al. https://doi.org/10.3390/geomatics3040027
18. Navigating geometric complexity in digital heritage: a review of AI-based semantic segmentation S. Battina https://doi.org/10.36680/j.itcon.2025.070
19. Edge Detection in 3D Point Clouds Using Digital Images M. Dolapsaki & A. Georgopoulos https://doi.org/10.3390/ijgi10040229
20. CLOI-NET: Class segmentation of industrial facilities’ point cloud datasets E. Agapaki & I. Brilakis https://doi.org/10.1016/j.aei.2020.101121
21. Knowledge-driven inference for automatic reconstruction of indoor detailed as-built BIMs from laser scanning data B. Xiong et al. https://doi.org/10.1016/j.autcon.2023.105097
22. Classification of ALS Point Clouds Using End-to-End Deep Learning L. Winiwarter et al. https://doi.org/10.1007/s41064-019-00073-0
23. Linear feature extraction from point cloud using color information Y. Alshawabkeh https://doi.org/10.1186/s40494-020-00371-6
24. From Acquisition to Presentation—The Potential of Semantics to Support the Safeguard of Cultural Heritage J. Ponciano et al. https://doi.org/10.3390/rs13112226
25. PointGrad: A Unified Spatially Varying Tensor Gradient Operator for Point Cloud Segmentation R. Bao et al. https://doi.org/10.1109/TGRS.2026.3686390
26. A target extraction method for 3D pig point clouds from a top-down perspective M. Li et al. https://doi.org/10.20517/ir.2026.17
27. A multi-scale fully convolutional network for semantic labeling of 3D point clouds M. Yousefhussien et al. https://doi.org/10.1016/j.isprsjprs.2018.03.018
28. A Comparative Study of Point-Based Deep Learning Techniques for Semantic Classification in Search and Rescue Arenas K. TURGUT & B. KALECİ https://doi.org/10.7240/jeps.897306
29. A Digital 4D Information System on the World Scale: Research Challenges, Approaches, and Preliminary Results S. Münster et al. https://doi.org/10.3390/app14051992
30. Large-Scale Metadata Processing for 3D Cultural Heritage Objects S. Münster https://doi.org/10.3390/land15050751
31. Damage Detection Based on 3D Point Cloud Data Processing from Laser Scanning of Conveyor Belt Surface P. Trybała et al. https://doi.org/10.3390/rs13010055
32. A 3D organized point cloud clustering algorithm for seismic fault data based on region growth L. Zhao et al. https://doi.org/10.1007/s10596-023-10259-6
33. Semantic feature-based point cloud segmentation method for tire tread J. Wang et al. https://doi.org/10.1016/j.measurement.2025.117199
34. DTNLS: 3D Point Cloud Segmentation Based on 2D Image and 3D Point Cloud Double Texture Feature Z. Liu et al. https://doi.org/10.1109/ACCESS.2024.3446593
35. Redundant Multi-Object Detection for Autonomous Vehicles in Structured Environments S. Feraco et al. https://doi.org/10.26552/com.C.2022.1.C1-C17
36. Ship detection and water level measurement system based on 3D point cloud Y. Chen et al. https://doi.org/10.1080/01431161.2024.2424509
37. Automated Storey Separation and Door and Window Extraction for Building Models from Complete Laser Scans K. Pexman et al. https://doi.org/10.3390/rs13173384
38. Power Line Extraction and Reconstruction Methods from Laser Scanning Data: A Literature Review N. Munir et al. https://doi.org/10.3390/rs15040973
39. An Experimental Analysis of Machine Learning Algorithms and Necessity of Classification System for Semantic Segmentation of Point Clouds for Heritage Buildings Y. Arayici & A. Gil https://doi.org/10.1145/3787223
40. Architectural Heritage Digitization: A Classification-Driven Semi-Automated Scan-to-HBIM Workflow R. Salah et al. https://doi.org/10.3390/buildings16010021
41. Multi-scale geometric variations semantic segmentation in Chinese architecture point clouds Y. Liu et al. https://doi.org/10.1038/s40494-025-02159-y
42. RadialNet: a point cloud classification approach using local structure representation with radial basis function Y. Ng et al. https://doi.org/10.1007/s11760-019-01607-0
43. Multichannel segmentation of planar point clouds using evolving curves L. Tomek et al. https://doi.org/10.1007/s40314-023-02457-w
44. Constant Size Point Cloud Clustering: A Compact, Non-Overlapping Solution A. Guarda et al. https://doi.org/10.1109/TMM.2020.2974325
45. Computer Vision-Based Measurement Techniques for Livestock Body Dimension and Weight: A Review W. Ma et al. https://doi.org/10.3390/agriculture14020306
46. Implementation of Object Detection Algorithms in the Inventory of Technical Infrastructure, Case Study of Utility Poles Detection M. Czyrzniak & J. Rapiński https://doi.org/10.59440/ceer/200378
47. Automatic part segmentation of facial anatomies using geometric deep learning toward a computer-aided facial rehabilitation D. Nguyen et al. https://doi.org/10.1016/j.engappai.2023.105832
48. A Point Cloud-Based Multiscale Fusion Segmentation Model for Surface Pore Structures in 3-D Printed Concrete Z. Ma et al. https://doi.org/10.1109/TIM.2026.3659673
49. Cantilever Structure Segmentation and Parameters Detection Based on Concavity and Convexity of 3-D Point Clouds Z. Han et al. https://doi.org/10.1109/TIM.2019.2930158
50. GeoAI: a review of artificial intelligence approaches for the interpretation of complex geomatics data R. Pierdicca & M. Paolanti https://doi.org/10.5194/gi-11-195-2022
51. Building Component Detection on Unstructured 3D Indoor Point Clouds Using RANSAC-Based Region Growing S. Oh et al. https://doi.org/10.3390/rs13020161
52. Application of computer vision techniques for 3D matching and retrieval of archaeological objects D. Jiménez-Badillo et al. https://doi.org/10.12688/f1000research.127095.2
53. Geometric characterization and segmentation of historic buildings using classification algorithms and convolutional networks in HBIM J. Moyano et al. https://doi.org/10.1016/j.autcon.2024.105728
54. Sharp Feature Detection as a Useful Tool in Smart Manufacturing J. Prochazkova et al. https://doi.org/10.3390/ijgi9070422
55. Color-Based Point Cloud Classification Using a Novel Gaussian Mixed Modeling-Based Approach versus a Deep Neural Network M. Štroner et al. https://doi.org/10.3390/rs16010115
56. Mesh2Brep: B-Rep Reconstruction via Robust Primitive Fitting and Intersection-Aware Constraints Z. Shen et al. https://doi.org/10.1109/TVCG.2025.3525844
57. Recent Advances and Perspectives in Deep Learning Techniques for 3D Point Cloud Data Processing Z. Ding et al. https://doi.org/10.3390/robotics12040100
58. Optimising 3D point cloud semantic segmentation: ML and manual refinement in the UNESCO Saltaire Village V. Cotella et al. https://doi.org/10.1080/09613218.2025.2521751
59. CSEANet: a 3D point cloud semantic segmentation model based on channel spatial point attention and edge information awareness H. Liu et al. https://doi.org/10.1080/01431161.2026.2682566
60. An Efficient Voxel-Based Segmentation Algorithm Based on Hierarchical Clustering to Extract LIDAR Power Equipment Data in Transformer Substations J. Guo et al. https://doi.org/10.1109/ACCESS.2020.3046313
61. FEC: Fast Euclidean Clustering for Point Cloud Segmentation Y. Cao et al. https://doi.org/10.3390/drones6110325
62. Automatic generation of synthetic heritage point clouds: Analysis and segmentation based on shape grammar for historical vaults C. Battini et al. https://doi.org/10.1016/j.culher.2023.10.003
63. Data enrichment for semantic segmentation of point clouds for the generation of geometric-semantic road models D. Crampen & J. Blankenbach https://doi.org/10.3389/fbuil.2025.1607375
64. A network-level sidewalk inventory method using mobile LiDAR and deep learning Q. Hou & C. Ai https://doi.org/10.1016/j.trc.2020.102772
65. A Segmentation Algorithm for Reconstruction of Decorations on Arm Part of Mongolian Buddha Statue Based on Medial Axis A. Renchin-ochir et al. https://doi.org/10.3756/artsci.18.28
66. Three-Dimensional X-Ray Computed Tomography Image Segmentation and Point Cloud Reconstruction for Internal Defect Identification in Laser Powder Bed Fused Parts B. Xu et al. https://doi.org/10.1115/1.4065179
67. Integration of an archaeological database in a virtual reality environment: Venta Micena, Orce (Granada, Spain) archaeological site J. González-Quiñones et al. https://doi.org/10.1080/20548923.2024.2375896
68. Multigranularity Multiclass-Layer Markov Random Field Model for Semantic Segmentation of Remote Sensing Images C. Zheng et al. https://doi.org/10.1109/TGRS.2020.3033293
69. Airborne LiDAR: state-of-the-art of system design, technology and application X. Li et al. https://doi.org/10.1088/1361-6501/abc867
70. 3D Shape Segmentation: A Review R. Li & Q. Peng https://doi.org/10.2174/1872212115666210203152106
71. Deep Learning-Based Classification of Large-Scale Airborne LiDAR Point Cloud M. Turgeon-Pelchat et al. https://doi.org/10.1080/07038992.2021.1927687
72. Segmentation of point clouds via joint semantic and geometric features for 3D modeling of the built environment Y. Perez-Perez et al. https://doi.org/10.1016/j.autcon.2021.103584
73. A Low-Cost High-Resolution LiDAR System With Nonrepetitive Scanning W. Luo & W. Wei https://doi.org/10.1109/TIM.2022.3181272
74. Autonomous construction of parameterizable 3D leaf models from scanned sweet pepper leaves with deep generative networks T. Moon et al. https://doi.org/10.1093/insilicoplants/diac015
75. Explainable machine learning framework for automated classification of structural objects in complex building façades Y. Yilmaz et al. https://doi.org/10.1177/01436244261479476
76. Point Cloud Classification Model Based on a Dual-Input Deep Network Framework R. Zhai et al. https://doi.org/10.1109/ACCESS.2020.2981357
77. Tightly Coupled, Graph-Based DVL/IMU Fusion and Decoupled Mapping for SLAM-Centric Maritime Infrastructure Inspection A. Thoms et al. https://doi.org/10.1109/JOE.2023.3265742
78. Leaf area extraction framework: Transformer-based segmentation and geometric-based completion approaches for accurate extraction of field maize leaf area from point clouds X. Peng et al. https://doi.org/10.1016/j.compag.2026.111793
79. 3D Fast Object Detection Based on Discriminant Images and Dynamic Distance Threshold Clustering B. Chen et al. https://doi.org/10.3390/s20247221
80. Three-Dimensional Reconstruction Techniques and the Impact of Lighting Conditions on Reconstruction Quality: A Comprehensive Review D. Rangelov et al. https://doi.org/10.3390/lights1010001
81. Enhancing 3D Gaussian splatting with semantic and geometric priors: bridging neural rendering and 3D city modeling D. Dai et al. https://doi.org/10.1080/13658816.2025.2608252
82. Virtual Disassembling of Historical Edifices: Experiments and Assessments of an Automatic Approach for Classifying Multi-Scalar Point Clouds into Architectural Elements A. Murtiyoso & P. Grussenmeyer https://doi.org/10.3390/s20082161
83. GPU-accelerated stochastic normal orientation Z. Zhang et al. https://doi.org/10.1016/j.cagd.2026.102554
84. Semi-automated reconstruction of HBIM from laser scan point clouds by integrating Scan-to-BIM and family library modeling Q. Wu et al. https://doi.org/10.1038/s40494-026-02673-7
85. A 3D Point Cloud Feature Identification Method Based on Improved Point Feature Histogram Descriptor C. Wang et al. https://doi.org/10.3390/electronics12173736
86. Scan2BIM-NET: Deep Learning Method for Segmentation of Point Clouds for Scan-to-BIM Y. Perez-Perez et al. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002132
87. AI-Powered Plant Science: Transforming Forestry Monitoring, Disease Prediction, and Climate Adaptation Z. Xu & D. Jiang https://doi.org/10.3390/plants14111626
88. TransWallNet: High-Performance Semantic Segmentation of Large-Scale and Multifeatured Point Clouds of Building Gables J. Ma et al. https://doi.org/10.1061/JCEMD4.COENG-14827
89. A Hierarchical unsupervised method for power line classification from airborne LiDAR data Y. Wang et al. https://doi.org/10.1080/17538947.2018.1503740
90. Comparison of 2D and 3D wall reconstruction algorithms from point cloud data for as-built BIM M. Bassier et al. https://doi.org/10.36680/j.itcon.2020.011
91. Multi-Normal Estimation via Pair Consistency Voting J. Zhang et al. https://doi.org/10.1109/TVCG.2018.2827998
92. Roadmap to semi-automatic generation of digital twins for brownfield process plants S. Sierla et al. https://doi.org/10.1016/j.jii.2021.100282
93. Automatic Threat Detection for Historic Buildings in Dark Places Based on the Modified OptD Method W. Błaszczak-Bąk et al. https://doi.org/10.3390/ijgi9020123
94. Automatic Workflow for Roof Extraction and Generation of 3D CityGML Models from Low-Cost UAV Image-Derived Point Clouds A. Murtiyoso et al. https://doi.org/10.3390/ijgi9120743
95. A Multilevel Multiresolution Machine Learning Classification Approach: A Generalization Test on Chinese Heritage Architecture K. Zhang et al. https://doi.org/10.3390/heritage5040204
96. An incremental facility location clustering with a new hybrid constrained pseudometric T. Bayer et al. https://doi.org/10.1016/j.patcog.2023.109520
97. Structural health monitoring based on three-dimensional point cloud technology: A systematic review Y. Zhang et al. https://doi.org/10.1016/j.rineng.2025.106552
98. Robot programming by demonstration: a novel system for robot trajectory programming based on robot operating system H. Zhang et al. https://doi.org/10.1007/s40436-020-00303-4
99. Single-Shot, Monochrome, Spatial Pixel-Encoded, Structured Light System for Determining Surface Orientations A. Elahi et al. https://doi.org/10.3390/photonics11111046
100. A literature survey of matrix methods for data science M. Stoll https://doi.org/10.1002/gamm.202000013
101. System of Automatic Recognition of Video Text Amazigh based on the Random Forest Y. Rachidi https://doi.org/10.33847/2686-8296.4.2_3
102. DAPnet: A Double Self-Attention Convolutional Network for Point Cloud Semantic Labeling L. Chen et al. https://doi.org/10.1109/JSTARS.2021.3113047
103. Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review S. Yang et al. https://doi.org/10.3390/rs15030548
104. Adaptive Clustering for Point Cloud Z. Lin et al. https://doi.org/10.3390/s24030848
105. ActivationNet: Representation Learning to Predict Contact Quality of Interacting 3D Surfaces in Engineering Designs R. Ranade & J. Pathak https://doi.org/10.1115/1.4053811
106. Coastal Sand Dunes Monitoring by Low Vegetation Cover Classification and Digital Elevation Model Improvement Using Synchronized Hyperspectral and Full-Waveform LiDAR Remote Sensing G. Frati et al. https://doi.org/10.3390/rs13010029
107. Classification of airborne 3D point clouds regarding separation of vegetation in complex environments D. Bulatov et al. https://doi.org/10.1364/AO.422973
108. Hierarchical SVM for Semantic Segmentation of 3D Point Clouds for Infrastructure Scenes M. Mansour et al. https://doi.org/10.3390/infrastructures9050083
109. Deep learning-based semantic segmentation of three-dimensional point cloud: a comprehensive review D. Singh & M. Yadav https://doi.org/10.1080/01431161.2023.2297177
110. Improving dynamic treatment unit forest planning with cellular automata heuristics W. Pär et al. https://doi.org/10.1007/s10342-022-01479-z
111. Contribution of Colour Information to the Classification of 3D Points from Aerial Images N. Yastikli & Z. Cetin https://doi.org/10.1007/s13369-023-08028-9
112. A Projection-based no-reference point cloud quality assessment metric based on perceptual features A. Goswami et al. https://doi.org/10.1016/j.displa.2025.103098
113. Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation Y. Xie et al. https://doi.org/10.1109/MGRS.2019.2937630
114. Vo-Norvana : Versatile Framework for Efficient Segmentation of Large Point Cloud Data Sets E. Che & M. Olsen https://doi.org/10.1061/JCCEE5.CPENG-4979
115. Wall Structure Geometry Verification Using TLS Data and BIM Model G. Bariczová et al. https://doi.org/10.3390/app112411804
116. Adversarial unsupervised domain adaptation for 3D semantic segmentation with multi-modal learning W. Liu et al. https://doi.org/10.1016/j.isprsjprs.2021.04.012
117. Hyperspectral lidar point cloud segmentation based on geometric and spectral information B. Chen et al. https://doi.org/10.1364/OE.27.024043
118. Classification of Point Clouds for Indoor Components Using Few Labeled Samples H. Wu et al. https://doi.org/10.3390/rs12142181
119. Robust Spacecraft Component Detection in Point Clouds Q. Wei et al. https://doi.org/10.3390/s18040933
120. A graph-based approach for simultaneous semantic and instance segmentation of plant 3D point clouds K. Mirande et al. https://doi.org/10.3389/fpls.2022.1012669
121. Unsupervised Segmentation of Point Clouds From Buildings Using Hierarchical Clustering Based on Gestalt Principles Y. Xu et al. https://doi.org/10.1109/JSTARS.2018.2817227
122. High-Precision defect detection and geometric verification in pipe jacking projects using computer vision and point cloud data H. Yan et al. https://doi.org/10.1016/j.rineng.2025.105358
123. Ontology of 3D virtual modeling in digital twin: a review, analysis and thinking Y. Wang et al. https://doi.org/10.1007/s10845-023-02246-6
124. Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey of Datasets and Methods B. Gao et al. https://doi.org/10.1109/TITS.2021.3076844
125. A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data A. Wróblewski et al. https://doi.org/10.3390/en15176302
126. Point Cloud Analysis of Railway Infrastructure: A Systematic Literature Review B. Dekker et al. https://doi.org/10.1109/ACCESS.2023.3337049
127. Towards Semantic Photogrammetry: Generating Semantically Rich Point Clouds from Architectural Close-Range Photogrammetry A. Murtiyoso et al. https://doi.org/10.3390/s22030966
128. Onsite Quality Check for Installation of Prefabricated Wall Panels Using Laser Scanning M. Wang et al. https://doi.org/10.3390/buildings11090412
129. Toward Building and Civil Infrastructure Reconstruction From Point Clouds: A Review on Data and Key Techniques Y. Xu & U. Stilla https://doi.org/10.1109/JSTARS.2021.3060568
130. Impact of 3D Digitising Technologies and Their Implementation P. Triviño-Tarradas et al. https://doi.org/10.3390/technologies12120260
131. Semi-Automated Segmentation of Geometric Shapes from Point Clouds R. Honti et al. https://doi.org/10.3390/rs14184591
132. Indoor Point Cloud Segmentation Based on Hierarchical Fusion of Structural Features Y. Zhou et al. https://doi.org/10.1109/ACCESS.2024.3417904
133. Iterative multilinear optimization for planar model fitting under geometric constraints J. Azorin-Lopez et al. https://doi.org/10.7717/peerj-cs.691
134. Efficient plane extraction using normal estimation and RANSAC from 3D point cloud L. Yang et al. https://doi.org/10.1016/j.csi.2021.103608
135. Robust Extraction of Multiple-Type Support Positioning Devices in the Catenary System of Railway Dataset Based on MLS Point Clouds Y. Zhang et al. https://doi.org/10.1109/TGRS.2023.3280208
136. Extracting of Cross Section Profiles from Complex Point Cloud Data Sets H. Kokab & R. Urbanic https://doi.org/10.1016/j.ifacol.2019.10.055
137. Enhanced normal estimation of point clouds via fine-grained geometric information learning W. Jin et al. https://doi.org/10.1007/s00138-025-01671-2
138. Research on Point Cloud Segmentation Method for Ancient Building Interior Scenes Based on Geometric Feature Multi-Scale Network J. Ma & D. Wu https://doi.org/10.3390/electronics15153409
139. Scale and Pose-Invariant Feature Quality Inspection for Freeform Geometries in Additive Manufacturing Y. Jin et al. https://doi.org/10.1115/1.4045174
140. Point Cloud vs. Mesh Features for Building Interior Classification M. Bassier et al. https://doi.org/10.3390/rs12142224
141. An Advanced Photogrammetric Solution to Measure Apples E. Grilli et al. https://doi.org/10.3390/rs13193960
142. Noise Model-Based Line Segmentation for Plane Extraction in Sparse 3-D LiDAR Data L. He et al. https://doi.org/10.1109/TGRS.2024.3394059
143. Integrating as-built BIM model from point cloud data in construction projects R. Zeng et al. https://doi.org/10.1108/ECAM-12-2022-1196
144. Three-dimensional segmentation of contacting soil particles using a superpoint multi-layer cross-attention transformer J. Xi et al. https://doi.org/10.1016/j.eswa.2025.130776
145. A comprehensive and hybrid approach to automatic and interactive point cloud segmentation using surface variation analysis and HDBSCAN clustering S. Sadaoui et al. https://doi.org/10.1016/j.cag.2025.104403
146. Attitude Estimation Method for Target Ships Based on LiDAR Point Clouds via An Improved RANSAC S. Wei et al. https://doi.org/10.3390/jmse11091755
147. LiDAR attribute based point cloud labeling using CNNs with 3D convolution layers M. Díaz-Medina et al. https://doi.org/10.1016/j.cageo.2023.105453
148. RFID-Based Vehicle Detection and Positioning for Autonomous Driving R. Hou et al. https://doi.org/10.1109/TIV.2026.3668860
149. Harnessing Deep Learning of Point Clouds for Morphology Mimicking of Universal 3D Shape‐Morphing Devices J. Wang et al. https://doi.org/10.1002/aisy.202400550
150. LiDAR in precision agriculture for orchards and perennial tree crops: bibliometric analysis, sensor technologies, and algorithmic workflows W. Liu et al. https://doi.org/10.1016/j.compag.2026.112049
151. DCG-Net: Dynamic Capsule Graph Convolutional Network for Point Clouds D. Bazazian & D. Nahata https://doi.org/10.1109/ACCESS.2020.3031812
152. CAD model reconstruction of spherical-jointed lattice structures from point clouds with discrete planar convex hulls B. Zhang et al. https://doi.org/10.1016/j.cad.2025.104030
153. A review of three dimensional reconstruction techniques J. Phang et al. https://doi.org/10.1007/s11042-021-10605-9
154. Multi-Scale Neighborhood Feature Extraction and Aggregation for Point Cloud Segmentation D. Li et al. https://doi.org/10.1109/TCSVT.2020.3023051
155. Fast and High Accuracy 3D Point Cloud Registration for Automatic Reconstruction From Laser Scanning Data A. Xu et al. https://doi.org/10.1109/ACCESS.2023.3270502
156. An Automated Sound Barrier Inventory Method Using Mobile LiDAR Q. Hou & C. Ai https://doi.org/10.1061/JTEPBS.0000732
157. Variational shape approximation of point set surfaces M. Skrodzki et al. https://doi.org/10.1016/j.cagd.2020.101875
158. A Visual Benchmark for Autonomous Driving in Open-Pit Mines Y. Li et al. https://doi.org/10.1109/TPAMI.2025.3632357
159. A Comparative Study for Indoor Planar Surface Segmentation via 3D Laser Point Cloud Data E. Eruyar et al. https://doi.org/10.34248/bsengineering.735705
160. Assessment of automatic segmentation accuracy with various point cloud density A. Yunusov et al. https://doi.org/10.22389/0016-7126-2020-961-7-47-55
161. Digital 3D Technologies for Humanities Research and Education: An Overview S. Muenster https://doi.org/10.3390/app12052426
162. A Framework for Drivable Area Detection Via Point Cloud Double Projection on Rough Roads F. Xu et al. https://doi.org/10.1007/s10846-021-01381-7
163. Close-Range Sensing and Data Fusion for Built Heritage Inspection and Monitoring—A Review E. Adamopoulos & F. Rinaudo https://doi.org/10.3390/rs13193936
164. MAPPING THE CONVERGENCE OF ARTIFICIAL INTELLIGENCE AND DIGITAL HERITAGE IN ARCHITECTURE: A COMPUTATIONAL TOPIC MODELING ANALYSIS OF EMERGING RESEARCH TRAJECTORIES (2016-2026) F. Akdağ https://doi.org/10.65520/erciyesfen.1932161
165. Deep learning based computer vision under the prism of 3D point clouds: a systematic review K. Tychola et al. https://doi.org/10.1007/s00371-023-03237-7
166. 3D point cloud processing and analysis: a survey A. Dehghanpour et al. https://doi.org/10.1007/s11042-026-21797-3
167. Автоматизированная сегментация и классификация данных мобильного лазерного сканирования для векторизации контурной части топографического плана городской территории М. Алтынцева et al. https://doi.org/10.33764/2411-1759-2024-29-6-32-43
168. PR-Alignment: Multidimensional Adaptive Registration Algorithm Based on Practical Application Scenarios W. Wang et al. https://doi.org/10.3390/machines11020254
169. Semantic Segmentation of Urban Airborne LiDAR Point Clouds Based on Fusion Attention Mechanism and Multi-Scale Features J. Wang et al. https://doi.org/10.3390/rs15215248
170. Incorporating Handcrafted Features into Deep Learning for Point Cloud Classification P. Hsu & Z. Zhuang https://doi.org/10.3390/rs12223713
171. Bridge point cloud semantic segmentation based on view consensus and cross-view self-prompt fusion Y. Zeng et al. https://doi.org/10.1016/j.autcon.2025.106003
172. Random Forest for video Text Amazigh Y. Rachidi & S. Krit https://doi.org/10.1051/e3sconf/202122901062
173. Methodology of Detection and Classification of Selected Aviation Obstacles Based on UAV Dense Image Matching M. Lalak & D. Wierzbicki https://doi.org/10.1109/JSTARS.2022.3149105
174. Generating LOD3 building models from structure-from-motion and semantic segmentation B. Pantoja-Rosero et al. https://doi.org/10.1016/j.autcon.2022.104430
175. Dense frustum-aware fusion for 3D object detection in perception systems Y. Deng et al. https://doi.org/10.1016/j.eswa.2023.122061
176. MM-PCQA+: Advancing Multi-Modal Learning for Point Cloud Quality Assessment Z. Zhang et al. https://doi.org/10.1145/3715134
177. A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification S. Teruggi et al. https://doi.org/10.3390/rs12162598
178. Tinto: Multisensor Benchmark for 3-D Hyperspectral Point Cloud Segmentation in the Geosciences A. Afifi et al. https://doi.org/10.1109/TGRS.2023.3340293
179. The Point Cloud Semantic Segmentation Method for the Ming and Qing Dynasties’ Official-Style Architecture Roof Considering the Construction Regulations Y. Dong et al. https://doi.org/10.3390/ijgi11040214
180. How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques N. Harandi et al. https://doi.org/10.1186/s13007-023-01031-z
181. Deep Learning on 3D Semantic Segmentation: A Detailed Review T. Betsas et al. https://doi.org/10.3390/rs17020298
182. Estimating Individual Conifer Seedling Height Using Drone-Based Image Point Clouds G. Castilla et al. https://doi.org/10.3390/f11090924
183. Hierarchical Optimization Segmentation and Parameter Extraction of Street Trees Based on Topology Checking and Boundary Analysis from LiDAR Point Clouds Y. Kou et al. https://doi.org/10.3390/s25010188
184. Pixel-level block classification and crack detection from 3D reconstruction models of masonry structures using convolutional neural networks D. Loverdos & V. Sarhosis https://doi.org/10.1016/j.engstruct.2024.118113
185. BIM-driven data augmentation method for semantic segmentation in superpoint-based deep learning network R. Zhai et al. https://doi.org/10.1016/j.autcon.2022.104373
186. From the Semantic Point Cloud to Heritage-Building Information Modeling: A Semiautomatic Approach Exploiting Machine Learning V. Croce et al. https://doi.org/10.3390/rs13030461
187. Backward Attentive Fusing Network With Local Aggregation Classifier for 3D Point Cloud Semantic Segmentation H. Shuai et al. https://doi.org/10.1109/TIP.2021.3073660
188. Active Iterative Optimization for Aerial Visual Reconstruction of Wide-Area Natural Environment H. Wang et al. https://doi.org/10.1109/TRO.2024.3475213
189. A Study on Automatic Registration of 3D Point Clouds Obtained from Archaeological Trench Investigations M. Enkhtugs et al. https://doi.org/10.3756/artsci.24.6_1
190. Automated extraction of structural planes and geometric information from point cloud F. Wang et al. https://doi.org/10.1177/13694332251340728
191. Point Cloud–Based Concrete Surface Defect Semantic Segmentation N. Bolourian et al. https://doi.org/10.1061/JCCEE5.CPENG-5009
192. Towards Real-Time 3D Editable Model Generation for Existing Indoor Building Environments on a Tablet A. Arnaud et al. https://doi.org/10.3389/frvir.2022.782564
193. Machine Learning for the Semi-Automatic 3D Decay Segmentation and Mapping of Heritage Assets R. Galantucci et al. https://doi.org/10.1080/15583058.2023.2287152
194. A new partitioning process for geometrical product specifications and verification N. Cai et al. https://doi.org/10.1016/j.precisioneng.2019.12.009
195. 3D Modeling of Urban Area Based on Oblique UAS Images—An End-to-End Pipeline V. Oniga et al. https://doi.org/10.3390/rs14020422
196. Parametric Classification of Furniture From Point Cloud Developed Using Low Cost Trolley Based Laser Scanning System S. Jafri et al. https://doi.org/10.1109/ACCESS.2023.3277007
197. Interplay of traditional methods and machine learning algorithms for tagging boosted objects C. Bose et al. https://doi.org/10.1140/epjs/s11734-024-01256-6
198. Depth-Image Segmentation Based on Evolving Principles for 3D Sensing of Structured Indoor Environments M. Antić et al. https://doi.org/10.3390/s21134395
199. Research on Point Cloud Segmentation Method Based on Local and Global Feature Extraction of Electricity Equipment Z. Zhang et al. https://doi.org/10.1109/ACCESS.2024.3468012
200. Разработка алгоритма классификации плотных облаков точек на примере городской застройки Д. Василенко https://doi.org/10.33764/2411-1759-2024-29-6-44-52
201. Advancements in Semantic Segmentation of 3D Point Clouds for Scene Understanding Using Deep Learning H. Benallal et al. https://doi.org/10.3390/technologies13080322
202. Processing of Large Underground Excavation System—Skeleton Based Section Segmentation for Point Cloud Regularization P. Dąbek et al. https://doi.org/10.3390/app16010313