11.2.4.4 Point Cloud Segmentation, Depth Object Segmentation

Chapter Contents (Back)
Segmentation, Range. Object Segmentation. Point Cloud Segmentation. Segment the data. Object detection and Segmentation are very similar.
See also Point Cloud Object Detection.
See also Semi-Supervised Object Detection, 3D Object Detection. More particularily:
See also Range and Color, RGB-D Segmentation and Analysis.
See also Depth Object Detection, 3D Object Detection.
See also Semantic Object Detection, 3D, Depth.

Yang, B.S.[Bi-Sheng], Dong, Z.[Zhen],
A shape-based segmentation method for mobile laser scanning point clouds,
PandRS(81), No. 1, July 2013, pp. 19-30.
Elsevier DOI 1306
Point classification; Object segmentation; Mobile laser scanning; Object extraction BibRef

Yang, B.S.[Bi-Sheng], Li, Y.H.[Yu-Hao], Zou, X.H.[Xiang-Hong], Dong, Z.[Zhen],
A Marker-free Calibration Method for Mobile Laser Scanning Point Clouds Correction,
ISPRS20(B2:347-354).
DOI Link 2012
BibRef

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Filtering airborne LiDAR data by embedding smoothness-constrained segmentation in progressive TIN densification,
PandRS(81), No. 1, July 2013, pp. 44-59.
Elsevier DOI 1306
Airborne LiDAR; Filtering; Progressive TIN densification; Point cloud segmentation; Segmentation using smoothness constraint BibRef

Vo, A.V.[Anh-Vu], Truong-Hong, L.[Linh], Laefer, D.F.[Debra F.], Bertolotto, M.[Michela],
Octree-based region growing for point cloud segmentation,
PandRS(104), No. 1, 2015, pp. 88-100.
Elsevier DOI 1505
Segmentation BibRef

Ben-Shabat, Y.[Yizhak], Avraham, T.[Tamar], Lindenbaum, M.[Michael], Fischer, A.[Anath],
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CVIU(174), 2018, pp. 12-23.
Elsevier DOI 1812
3D point cloud over-segmentation, 3D point cloud segmentation, Super-points, Grouping BibRef

Zhao, B.F.[Bu-Fan], Hua, X.H.[Xiang-Hong], Yu, K.G.[Ke-Gen], Xuan, W.[Wei], Chen, X.J.[Xi-Jiang], Tao, W.Y.[Wu-Yong],
Indoor Point Cloud Segmentation Using Iterative Gaussian Mapping and Improved Model Fitting,
GeoRS(58), No. 11, November 2020, pp. 7890-7907.
IEEE DOI 2011
Machine learning, Feature extraction, Convolution, Laser modes, Shape, Fitting, 3-D point cloud, segmentation BibRef

Zhang, S., Cui, S., Ding, Z.,
Hypergraph Spectral Clustering for Point Cloud Segmentation,
SPLetters(27), 2020, pp. 1655-1659.
IEEE DOI 1806
Tensile stress, Frequency estimation, Estimation, Covariance matrices, Laplace equations, Hypergraph, spectral clustering BibRef

Lei, H.[Huan], Akhtar, N.[Naveed], Mian, A.[Ajmal],
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds,
PAMI(43), No. 10, October 2021, pp. 3664-3680.
IEEE DOI 2109
BibRef
Earlier:
SegGCN: Efficient 3D Point Cloud Segmentation With Fuzzy Spherical Kernel,
CVPR20(11608-11617)
IEEE DOI 2008
BibRef
Earlier:
Octree Guided CNN With Spherical Kernels for 3D Point Clouds,
CVPR19(9623-9632).
IEEE DOI 2002
Kernel, Convolution, Neural networks, Feature extraction, Semantics, semantic segmentation. Convolutional codes, Integrated circuits, Robustness BibRef

Li, X.O.[Xia-Ohan], Chen, L.[Lu], Li, S.[Shuang], Zhou, X.[Xiang],
Depth segmentation in real-world scenes based on U-V disparity analysis,
JVCIR(73), 2020, pp. 102920.
Elsevier DOI 2012
Depth scene segmentation, U-V disparity map, Projection characteristics analysis, Object detection, RANSAC algorithm BibRef

Guarda, A.F.R.[André F. R.], Rodrigues, N.M.M.[Nuno M. M.], Pereira, F.[Fernando],
Constant Size Point Cloud Clustering: A Compact, Non-Overlapping Solution,
MultMed(23), 2021, pp. 77-91.
IEEE DOI 2012
Clustering algorithms, Clustering methods, Transform coding, Encoding, Image segmentation, Complexity theory, Point cloud, non-overlapping BibRef

Ma, L., Li, Y., Li, J., Tan, W., Yu, Y., Chapman, M.A.,
Multi-Scale Point-Wise Convolutional Neural Networks for 3D Object Segmentation From LiDAR Point Clouds in Large-Scale Environments,
ITS(22), No. 2, February 2021, pp. 821-836.
IEEE DOI 2102
Feature extraction, Semantics, Shape, Solid modeling, Neural networks, Roads, Point clouds, k-nearest neighbor BibRef

Geng, X.X.[Xiao-Xiao], Ji, S.P.[Shun-Ping], Lu, M.[Meng], Zhao, L.L.[Ling-Li],
Multi-Scale Attentive Aggregation for LiDAR Point Cloud Segmentation,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Luo, N.[Nan], Yu, H.Q.[Hong-Quan], Huo, Z.F.[Zhen-Feng], Liu, J.H.[Jin-Hui], Wang, Q.[Quan], Xu, Y.[Ying], Gao, Y.[Yun],
KVGCN: A KNN Searching and VLAD Combined Graph Convolutional Network for Point Cloud Segmentation,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Li, D.W.[Da-Wei], Shi, G.L.[Guo-Liang], Wu, Y.H.[Yu-Hao], Yang, Y.P.[Yan-Ping], Zhao, M.B.[Ming-Bo],
Multi-Scale Neighborhood Feature Extraction and Aggregation for Point Cloud Segmentation,
CirSysVideo(31), No. 6, June 2021, pp. 2175-2191.
IEEE DOI 2106
Feature extraction, Semantics, Image segmentation, Data mining, point cloud segmentation BibRef

Chen, C.F.[Chao-Fan], Qian, S.S.[Sheng-Sheng], Fang, Q.[Quan], Xu, C.S.[Chang-Sheng],
HAPGN: Hierarchical Attentive Pooling Graph Network for Point Cloud Segmentation,
MultMed(23), 2021, pp. 2335-2346.
IEEE DOI 2108
Feature extraction, Task analysis, Layout, Logic gates, Machine learning, gated graph attention network BibRef

Guo, Y.L.[Yu-Lan], Wang, H.Y.[Han-Yun], Hu, Q.Y.[Qing-Yong], Liu, H.[Hao], Liu, L.[Li], Bennamoun, M.[Mohammed],
Deep Learning for 3D Point Clouds: A Survey,
PAMI(43), No. 12, December 2021, pp. 4338-4364.
IEEE DOI 2112
Solid modeling, Deep learning, Object detection, Laser radar, Task analysis, Sensors, Deep learning, part segmentation BibRef

Yang, F.[Fei], Davoine, F.[Franck], Wang, H.[Huan], Jin, Z.[Zhong],
Continuous conditional random field convolution for point cloud segmentation,
PR(122), 2022, pp. 108357.
Elsevier DOI 2112
Point cloud segmentation, Conditional random fields, Message passing, Graph convolution, Mean-field approximation BibRef

Huang, H.[Hao], Li, X.[Xiang], Wang, L.J.[Ling-Jing], Fang, Y.[Yi],
3D-MetaConNet: Meta-learning for 3D Shape Classification and Segmentation,
3DV21(982-991)
IEEE DOI 2201
Training, Representation learning, Adaptation models, Solid modeling, Shape, Computational modeling BibRef

Jing, W.P.[Wei-Peng], Zhang, W.J.[Wen-Jun], Li, L.H.[Lin-Hui], Di, D.L.[Dong-Lin], Chen, G.S.[Guang-Sheng], Wang, J.[Jian],
AGNet: An Attention-Based Graph Network for Point Cloud Classification and Segmentation,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Zhao, C.[Chen], Yang, J.Q.[Jia-Qi], Xiong, X.[Xin], Zhu, A.F.[Ang-Fan], Cao, Z.G.[Zhi-Guo], Li, X.[Xin],
Rotation invariant point cloud analysis: Where local geometry meets global topology,
PR(127), 2022, pp. 108626.
Elsevier DOI 2205
Point cloud analysis, Rotation invariance, Deep learning, Classification, Segmentation BibRef

Xu, B.[Bo], Chen, Z.[Zhen], Zhu, Q.[Qing], Ge, X.M.[Xu-Ming], Huang, S.Z.[Sheng-Zhi], Zhang, Y.T.[Ye-Ting], Liu, T.Y.[Tian-Yang], Wu, D.[Di],
Geometrical Segmentation of Multi-Shape Point Clouds Based on Adaptive Shape Prediction and Hybrid Voting RANSAC,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Song, Z.J.[Zhan-Jie], Zhao, L.Q.[Lin-Qing], Zhou, J.[Jie],
Learning Hybrid Semantic Affinity for Point Cloud Segmentation,
CirSysVideo(32), No. 7, July 2022, pp. 4599-4612.
IEEE DOI 2207
Semantics, Point cloud compression, Image segmentation, Solid modeling, Task analysis, Learning systems, graph convolutional network BibRef

Zhu, X.G.[Xin-Ge], Zhou, H.[Hui], Wang, T.[Tai], Hong, F.Z.[Fang-Zhou], Li, W.[Wei], Ma, Y.X.[Yue-Xin], Li, H.S.[Hong-Sheng], Yang, R.G.[Rui-Gang], Lin, D.[Dahua],
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-Based Perception,
PAMI(44), No. 10, October 2022, pp. 6807-6822.
IEEE DOI 2209
BibRef
Earlier: A1, A2, A3, A4, A6, A5, A7, A9:
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation,
CVPR21(9934-9943)
IEEE DOI 2111
Laser radar, Convolution, Feature extraction, Gold, Task analysis, Solid modeling, Cylindrical partition, asymmetrical convolution, point cloud panoptic segmentation. Solid modeling, Network topology, Interference, Encoding BibRef

Zheng, Y.[Yu], Xu, X.W.[Xiu-Wei], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
PointRas: Uncertainty-Aware Multi-Resolution Learning for Point Cloud Segmentation,
IP(31), 2022, pp. 6002-6016.
IEEE DOI 2209
Point cloud compression, Decoding, Signal resolution, Shape, Interpolation, Semantics, Point cloud segmentation, contextual learning BibRef

Wang, Z.Y.[Zi-Yi], Rao, Y.M.[Yong-Ming], Yu, X.[Xumin], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
Point-to-Pixel Prompting for Point Cloud Analysis With Pre-Trained Image Models,
PAMI(46), No. 6, June 2024, pp. 4381-4397.
IEEE DOI 2405
Point cloud compression, Task analysis, Solid modeling, Tuning, Analytical models, Feature extraction, Distillation, point cloud, prompt tuning BibRef

Xu, X.W.[Xiu-Wei], Wang, Z.W.[Zi-Wei], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
Back to Reality: Learning Data-Efficient 3D Object Detector with Shape Guidance,
PAMI(46), No. 2, February 2024, pp. 1165-1180.
IEEE DOI 2401
Object detection, Shape, Point cloud compression BibRef

Zheng, Y.[Yu], Duan, Y.[Yueqi], Lu, J.W.[Ji-Wen], Zhou, J.[Jie], Tian, Q.[Qi],
HyperDet3D: Learning a Scene-conditioned 3D Object Detector,
CVPR22(5575-5584)
IEEE DOI 2210
Face recognition, Object detection, Detectors, Benchmark testing, Libraries, 3D from multi-view and sensors, retrieval BibRef

Wei, Y.[Yi], Wei, Z.[Zibu], Rao, Y.M.[Yong-Ming], Li, J.X.[Jia-Xin], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection,
ECCV22(XXIX:179-195).
Springer DOI 2211
BibRef

Xu, X.W.[Xiu-Wei], Wang, Y.F.[Yi-Fan], Zheng, Y.[Yu], Rao, Y.M.[Yong-Ming], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
Back to Reality: Weakly-supervised 3D Object Detection with Shape-Guided Label Enhancement,
CVPR22(8428-8437)
IEEE DOI 2210
Training, Annotations, Shape, Layout, Object detection, Detectors, 3D from multi-view and sensors, Recognition: detection, retrieval BibRef

Rao, Y.M.[Yong-Ming], Liu, B.[Benlin], Wei, Y.[Yi], Lu, J.W.[Ji-Wen], Hsieh, C.J.[Cho-Jui], Zhou, J.[Jie],
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection,
ICCV21(3263-3272)
IEEE DOI 2203
Solid modeling, Semantics, Layout, Training data, Object detection, Benchmark testing, Detection and localization in 2D and 3D, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Zheng, Y.[Yu], Zhang, D.Y.[Dan-Yang], Xie, S.[Sinan], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Rotation-Robust Intersection over Union for 3d Object Detection,
ECCV20(XX:464-480).
Springer DOI 2011
BibRef

Wang, Z.Y.[Zi-Yi], Rao, Y.M.[Yong-Ming], Yu, X.[Xumin], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation,
CVPR22(11809-11819)
IEEE DOI 2210
Point cloud compression, Image segmentation, Fuses, Semantics, Transforms, Transformers, Segmentation, 3D from multi-view and sensors BibRef

Honti, R.[Richard], Erdélyi, J.[Ján], Kopácik, A.[Alojz],
Semi-Automated Segmentation of Geometric Shapes from Point Clouds,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Zoumpekas, T.[Thanasis], Salamó, M.[Maria], Puig, A.[Anna],
Rethinking Design and Evaluation of 3D Point Cloud Segmentation Models,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Luo, Z.W.[Zi-Wei], Xie, Z.[Zhong], Wan, J.[Jie], Zeng, Z.Y.[Zi-Yin], Liu, L.[Lu], Tao, L.[Liufeng],
Indoor 3D Point Cloud Segmentation Based on Multi-Constraint Graph Clustering,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Xiao, K.[Kai], Qian, J.[Jia], Li, T.[Teng], Peng, Y.X.[Yuan-Xi],
Multispectral LiDAR Point Cloud Segmentation for Land Cover Leveraging Semantic Fusion in Deep Learning Network,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Gao, Y.B.[Yong-Bin], Liu, X.B.[Xue-Bing], Li, J.[Jun], Fang, Z.J.[Zhi-Jun], Jiang, X.Y.[Xiao-Yan], Huq, K.M.S.[Kazi Mohammed Saidul],
LFT-Net: Local Feature Transformer Network for Point Clouds Analysis,
ITS(24), No. 2, February 2023, pp. 2158-2168.
IEEE DOI 2302
Point cloud compression, Transformers, Task analysis, Feature extraction, Convolution, Semantics, 6G, point cloud, segmentation BibRef

Chen, H.[Hui], Xie, T.T.[Ting-Ting], Liang, M.[Man], Liu, W.Q.[Wan-Quan], Liu, P.X.P.[Peter Xiao-Ping],
A local tangent plane distance-based approach to 3D point cloud segmentation via clustering,
PR(137), 2023, pp. 109307.
Elsevier DOI 2302
3D point cloud, Plane segmentation, Tangent distance, Adaptive clustering BibRef

Zhang, W.J.[Wen Jing], Su, S.Z.[Song Zhi], Hong, Q.Q.[Qing Qi], Wang, B.Z.[Bei Zhan], Sun, L.[Li],
Long short-distance topology modelling of 3D point cloud segmentation with a graph convolution neural network,
IET-CV(17), No. 3, 2023, pp. 251-264.
DOI Link 2305
BibRef

Ye, S.Q.[Shu-Quan], Chen, D.D.[Dong-Dong], Han, S.F.[Song-Fang], Liao, J.[Jing],
Robust Point Cloud Segmentation With Noisy Annotations,
PAMI(45), No. 6, June 2023, pp. 7696-7710.
IEEE DOI 2305
BibRef
Earlier:
Learning with Noisy Labels for Robust Point Cloud Segmentation,
ICCV21(6423-6432)
IEEE DOI 2203
Noise measurement, Point cloud compression, Task analysis, Image segmentation, Annotations, Image edge detection, Point cloud, noisy label. Correlation, Upper bound, Lead, Robustness, Optimization and learning methods, 3D from multiview and other sensors BibRef

Ye, S.Q.[Shu-Quan], Xu, Y.[Yan], Chen, D.D.[Dong-Dong], Han, S.F.[Song-Fang], Liao, J.[Jing],
Learning a Single Network for Robust Medical Image Segmentation With Noisy Labels,
MedImg(43), No. 9, September 2024, pp. 3188-3199.
IEEE DOI 2409
Noise measurement, Image edge detection, Noise, Image segmentation, Biomedical imaging, Reliability, Annotations, label denoising BibRef

Liu, Y.F.[Yi-Fan], Li, W.Y.[Wu-Yang], Liu, J.[Jie], Chen, H.[Hui], Yuan, Y.X.[Yi-Xuan],
GRAB-Net: Graph-Based Boundary-Aware Network for Medical Point Cloud Segmentation,
MedImg(42), No. 9, September 2023, pp. 2776-2786.
IEEE DOI 2310
BibRef

Tan, X.[Xin], Ma, Q.H.[Qi-Hang], Gong, J.Y.[Jing-Yu], Xu, J.C.[Jia-Chen], Zhang, Z.Z.[Zhi-Zhong], Song, H.C.[Hai-Chuan], Qu, Y.Y.[Yan-Yun], Xie, Y.[Yuan], Ma, L.Z.[Li-Zhuang],
Positive-Negative Receptive Field Reasoning for Omni-Supervised 3D Segmentation,
PAMI(45), No. 12, December 2023, pp. 15328-15344.
IEEE DOI 2311
BibRef
Earlier: A3, A4, A1, A6, A7, A8, A9, Only:
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning,
CVPR21(11668-11677)
IEEE DOI 2111
Codes, Semantics, Neural networks, Benchmark testing, Cognition, Entropy BibRef

Zhu, G.[Guanyu], Zhou, Y.[Yong], Yao, R.[Rui], Zhu, H.C.[Han-Cheng],
Cross-Class Bias Rectification for Point Cloud Few-Shot Segmentation,
MultMed(25), 2023, pp. 9175-9188.
IEEE DOI 2312
BibRef

Zhu, G.[Guanyu], Zhou, Y.[Yong], Yao, R.[Rui], Zhu, H.C.[Han-Cheng],
Information Gap Narrowing for Point Cloud Few-Shot Segmentation,
CirSysVideo(34), No. 6, June 2024, pp. 4421-4433.
IEEE DOI 2406
Point cloud compression, Prototypes, Task analysis, Feature extraction, Data models, Prediction algorithms, co-occurrent objects BibRef

Su, Y.Y.[Yong-Yi], Xu, X.[Xun], Jia, K.[Kui],
Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning,
CirSysVideo(33), No. 12, December 2023, pp. 7723-7736.
IEEE DOI 2312
BibRef

Zhang, X.Y.[Xin-Yuan], Han, F.[Fei], Shen, S.[Shiyang], Wang, Y.C.[Yi-Cheng], Xu, S.[Shilong], Dong, X.[Xiao], Hu, Y.H.[Yi-Hua],
Target region extraction and segmentation algorithm for reflective tomography Lidar image,
IET-IPR(17), No. 4, 2023, pp. 1001-1009.
DOI Link 2303
image segmentation, Lidar, reflective tomography, target region extraction BibRef

Wen, S.[Shuhuan], Li, P.J.[Peng-Jiang], Zhang, H.[Hong],
Hybrid Cross-Transformer-KPConv for Point Cloud Segmentation,
SPLetters(31), 2024, pp. 126-130.
IEEE DOI 2401
BibRef

Xiao, A.[Aoran], Guan, D.[Dayan], Zhang, X.Q.[Xiao-Qin], Lu, S.J.[Shi-Jian],
Domain Adaptive LiDAR Point Cloud Segmentation With 3D Spatial Consistency,
MultMed(26), 2024, pp. 5536-5547.
IEEE DOI 2404
Point cloud compression, Laser radar, Training, Adaptation models, Perturbation methods, Task analysis, LiDAR point clouds, deep learning BibRef

Xiao, A.[Aoran], Huang, J.X.[Jia-Xing], Liu, K.C.[Kang-Cheng], Guan, D.[Dayan], Zhang, X.Q.[Xiao-Qin], Lu, S.J.[Shi-Jian],
Domain Adaptive LiDAR Point Cloud Segmentation via Density-Aware Self-Training,
ITS(25), No. 10, October 2024, pp. 13627-13639.
IEEE DOI 2410
Point cloud compression, Laser radar, Labeling, Adaptation models, Training, Semantic segmentation, LiDAR point cloud, deep learning BibRef

Jiang, Y.[Yun], Liu, B.X.[Bing-Xi], Zhang, Z.Q.[Ze-Qun], Yan, Y.[Yao], Guo, H.[Huanting], Li, Y.H.[Yu-Hang],
Dense-sparse representation matters: A point-based method for volumetric medical image segmentation,
JVCIR(100), 2024, pp. 104115.
Elsevier DOI 2405
BibRef
And: Corrigendum: JVCIR(102), 2024, pp. 104205.
Elsevier DOI 2407
Convolutional neural networks, Transformer, Volumetric images, Point cloud BibRef

Umam, A.[Ardian], Yang, C.K.[Cheng-Kun], Chuang, J.H.[Jen-Hui], Lin, Y.Y.[Yen-Yu],
Unsupervised Point Cloud Co-Part Segmentation via Co-Attended Superpoint Generation and Aggregation,
MultMed(26), 2024, pp. 7775-7786.
IEEE DOI 2405
Point cloud compression, Semantics, Shape, Image segmentation, Task analysis, Annotations, Point cloud segmentation, unsupervised learning BibRef

Zhu, Q.F.[Qin-Feng], Fan, L.[Lei], Weng, N.X.[Ning-Xin],
Advancements in point cloud data augmentation for deep learning: A survey,
PR(153), 2024, pp. 110532.
Elsevier DOI 2405
Point cloud, Augmentation, Deep learning, Detection, Segmentation, Classification BibRef

Wu, Z.H.[Zhong-Hua], Wu, Y.C.[Yi-Cheng], Lin, G.S.[Guo-Sheng], Cai, J.F.[Jian-Fei],
Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud Segmentation,
IJCV(132), No. 6, June 2024, pp. 2276-2289.
Springer DOI 2406
BibRef

Wei, J.C.[Jia-Cheng], Lin, G.S.[Guo-Sheng], Yap, K.H.[Kim-Hui], Liu, F.[Fayao], Hung, T.Y.[Tzu-Yi],
Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds,
CirSysVideo(34), No. 6, June 2024, pp. 4367-4377.
IEEE DOI 2406
Point cloud compression, Training, Semantic segmentation, Labeling, Decoding, Convolution, 3D point cloud, weakly supervised learning, semantic segmentation BibRef

Wu, Z.H.[Zhong-Hua], Wu, Y.C.[Yi-Cheng], Lin, G.S.[Guo-Sheng], Cai, J.F.[Jian-Fei], Qian, C.[Chen],
Dual Adaptive Transformations for Weakly Supervised Point Cloud Segmentation,
ECCV22(XXXI:78-96).
Springer DOI 2211
BibRef

Saltori, C.[Cristiano], Galasso, F.[Fabio], Fiameni, G.[Giuseppe], Sebe, N.[Nicu], Poiesi, F.[Fabio], Ricci, E.[Elisa],
Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation,
PAMI(45), No. 12, December 2023, pp. 14234-14247.
IEEE DOI 2311
BibRef
Earlier: A1, A2 A3, A4, A6, A5:
CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation,
ECCV22(XXXIII:586-602).
Springer DOI 2211
BibRef

Saltori, C.[Cristiano], Krivosheev, E.[Evgeny], Lathuiliére, S.[Stéphane], Sebe, N.[Nicu], Galasso, F.[Fabio], Fiameni, G.[Giuseppe], Ricci, E.[Elisa], Poiesi, F.[Fabio],
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation,
ECCV22(XXXIII:567-585).
Springer DOI 2211
BibRef

Xie, T.T.[Ting-Ting], Chen, H.[Hui], Liu, W.Q.[Wan-Quan], Zhou, R.Y.[Rong-Yu], Li, Q.[Qilin],
3D surface segmentation from point clouds via quadric fits based on DBSCAN clustering,
PR(154), 2024, pp. 110589.
Elsevier DOI 2406
3D point clouds, Surface extraction, DBSCAN, Quadric surface BibRef

Liu, B.[Bo], Zeng, H.[Hui], Dong, Q.[Qiulei], Hu, Z.Y.[Zhan-Yi],
Language-Level Semantics-Conditioned 3D Point Cloud Segmentation,
RS(16), No. 13, 2024, pp. 2376.
DOI Link 2407
BibRef

Kumar, P.[Prashant], Makwana, D.[Dhruv], Susladkar, O.[Onkar], Mittal, A.[Anurag], Kalra, P.K.[Prem Kumar],
MOVES: Movable and moving LiDAR scene segmentation in label-free settings using static reconstruction,
PR(155), 2024, pp. 110651.
Elsevier DOI 2408
Label-free LiDAR segmentation, Static LiDAR reconstruction, Dynamic environments BibRef

Wang, X.[Xuchu], Yuan, Y.[Yue],
MNAT-Net: Multi-Scale Neighborhood Aggregation Transformer Network for Point Cloud Classification and Segmentation,
ITS(25), No. 8, August 2024, pp. 9153-9167.
IEEE DOI 2408
Point cloud compression, Transformers, Feature extraction, Task analysis, Natural language processing, Convolution, transformer BibRef

Xie, K.[Kai], Zhu, J.Z.[Jian-Zhong], Ren, H.[He], Wang, Y.H.[Ying-Hua], Yang, W.[Wanneng], Chen, G.[Gang], Lin, C.[Chengda], Zhai, R.[Ruifang],
Delving into the Potential of Deep Learning Algorithms for Point Cloud Segmentation at Organ Level in Plant Phenotyping,
RS(16), No. 17, 2024, pp. 3290.
DOI Link 2409
BibRef

Song, Z.Y.[Zi-Yang], Yang, B.[Bo],
Unsupervised 3D Object Segmentation of Point Clouds by Geometry Consistency,
PAMI(46), No. 12, December 2024, pp. 8459-8473.
IEEE DOI 2411
Point cloud compression, Object segmentation, Motion segmentation, Annotations, Geometry, Vectors, unsupervised learning BibRef

Du, Z.J.[Zi-Jin], Liang, J.Q.[Jian-Qing], Liang, J.[Jiye], Yao, K.X.[Kai-Xuan], Cao, F.L.[Fei-Long],
Graph Regulation Network for Point Cloud Segmentation,
PAMI(46), No. 12, December 2024, pp. 7940-7955.
IEEE DOI 2411
Point cloud compression, Feature extraction, Prototypes, Convolution, Regulation, Transformers, Graph, heterophily, homophily, segmentation BibRef

Zhuang, X.W.[Xian-Wei], Wang, H.[Hualiang], He, X.X.[Xiao-Xuan], Fu, S.[Siming], Hu, H.J.[Hao-Ji],
SemiGMMPoint: Semi-supervised point cloud segmentation based on Gaussian mixture models,
PR(158), 2025, pp. 111045.
Elsevier DOI Code:
WWW Link. 2411
3D point cloud segmentation, Semi-supervised learning, Generative classifier, Gaussian mixture models, Contrastive learning BibRef

Lin, J.X.[Jing-Xin], Zhong, K.F.[Kai-Fan], Gong, T.[Tao], Zhang, X.M.[Xian-Min], Wang, N.F.[Nian-Feng],
Point Cloud Segmentation Neural Network with Same-Type Point Cloud Assistance,
IVC(152), 2024, pp. 105331.
Elsevier DOI 2412
Neural network, Same-type point cloud, Point cloud segmentation BibRef

Chen, M.[Meida], Han, K.[Kangle], Yu, Z.[Zifan], Feng, A.[Andrew], Hou, Y.[Yu], You, S.[Suya], Soibelman, L.[Lucio],
An Aerial Photogrammetry Benchmark Dataset for Point Cloud Segmentation and Style Translation,
RS(16), No. 22, 2024, pp. 4240.
DOI Link 2412
BibRef

Shu, Z.Y.[Zhen-Yu], Li, S.[Shiyang], Xin, S.Q.[Shi-Qing], Liu, L.G.[Li-Gang],
3D Shape Segmentation With Potential Consistency Mining and Enhancement,
MultMed(27), 2025, pp. 133-144.
IEEE DOI 2501
Shape, Feature extraction, Faces, Vectors, Point cloud compression, Partitioning algorithms, Labeling, Data mining, Accuracy, shape analysis BibRef


Ošep, A.[Aljoša], Meinhardt, T.[Tim], Ferroni, F.[Francesco], Peri, N.[Neehar], Ramanan, D.[Deva], Leal-Taixé, L.[Laura],
Better Call Sal: Towards Learning to Segment Anything in Lidar,
ECCV24(XXXIX: 71-90).
Springer DOI 2412
BibRef

Xu, R.J.[Rui-Jie], Zhang, C.[Chuyu], Ren, H.[Hui], He, X.M.[Xu-Ming],
Dual-level Adaptive Self-labeling for Novel Class Discovery in Point Cloud Segmentation,
ECCV24(XIII: 288-305).
Springer DOI 2412
BibRef

Zou, T.[Tianpei], Qu, S.Q.[San-Qing], Li, Z.J.[Zhi-Jun], Knoll, A.[Alois], He, L.[Lianghua], Chen, G.[Guang], Jiang, C.J.[Chang-Jun],
HGL: Hierarchical Geometry Learning for Test-time Adaptation in 3d Point Cloud Segmentation,
ECCV24(LV: 19-36).
Springer DOI 2412
BibRef

Peng, X.[Xidong], Chen, R.[Runnan], Qiao, F.[Feng], Kong, L.D.[Ling-Dong], Liu, Y.[Youquan], Sun, Y.J.[Yu-Jing], Wang, T.[Tai], Zhu, X.G.[Xin-Ge], Ma, Y.X.[Yue-Xin],
Learning to Adapt Sam for Segmenting Cross-domain Point Clouds,
ECCV24(XLIII: 54-71).
Springer DOI 2412
BibRef

Zhang, Z.Y.[Zhi-Yuan], Yang, L.C.[Li-Cheng], Xiang, Z.Y.[Zhi-Yu],
Risurconv: Rotation Invariant Surface Attention-augmented Convolutions for 3D Point Cloud Classification and Segmentation,
ECCV24(XXVIII: 93-109).
Springer DOI 2412
BibRef

Li, L.[Li], Shum, H.P.H.[Hubert P. H.], Breckon, T.P.[Toby P.],
Rapid-SEG: Range-aware Pointwise Distance Distribution Networks for 3d Lidar Segmentation,
ECCV24(VII: 222-241).
Springer DOI 2412
BibRef

Yamaguchi, M.[Masahiro], Higa, K.[Kyota], Hosoi, T.[Toshinori], Shibata, T.[Takashi],
Robust 3D Semantic Segmentation with Incomplete Point Clouds Based on Sequential Frame Sampling,
ICIP24(3526-3532)
IEEE DOI 2411
Point cloud compression, Semantic segmentation, Employment, Semantics, Indoor environment, Safety, 3D Semantic Segmentation, Incomplete Point Clouds BibRef

Stearns, C.[Colton], Fu, A.[Alex], Liu, J.[Jiateng], Park, J.J.[Jeong Joon], Rempe, D.[Davis], Paschalidou, D.[Despoina], Guibas, L.J.[Leonidas J.],
CurveCloudNet: Processing Point Clouds with 1D Structure,
CVPR24(27981-27991)
IEEE DOI 2410
Point cloud compression, Laser radar, Accuracy, Cognition, Sensors, point cloud, 3D perception, LiDAR, 3D segmentation, autonomous vehicles BibRef

Janda, A.[Andrej], Wagstaff, B.[Brandon], Ng, E.G.[Edwin G.], Kelly, J.[Jonathan],
Contrastive Learning for Self-Supervised Pre-Training of Point Cloud Segmentation Networks With Image Data,
CRV23(145-152)
IEEE DOI 2406
Point cloud compression, Training, Visualization, Solid modeling, Annotations, Semantic segmentation, self supervised, pre training, point cloud segmentation BibRef

Cho, W.W.[Won-Woo], Choi, D.[Dongmin], Lim, H.[Hyesu], Choi, J.H.[Jin-Ho], Choi, S.[Saemee], Min, H.S.[Hyun-Seok], Lim, S.[Sungbin], Choo, J.[Jaegul],
Slice and Conquer: A Planar-to-3D Framework for Efficient Interactive Segmentation of Volumetric Images,
WACV24(7599-7608)
IEEE DOI 2404
Image segmentation, Shape, Pipelines, Human in the loop, Space exploration, Applications, Image recognition and understanding BibRef

Sun, H.[Haowen], Duan, Y.[Yueqi], Yan, J.C.[Jun-Cheng], Liu, Y.F.[Yi-Fan], Lu, J.W.[Ji-Wen],
MirageRoom: 3D Scene Segmentation with 2D Pre-Trained Models by Mirage Projection,
CVPR24(20237-20246)
IEEE DOI 2410
Point cloud compression, Solid modeling, Image segmentation, Cameras, 3D point cloud, mirage projection BibRef

Tang, P.[Pin], Xu, H.M.[Hai-Ming], Ma, C.[Chao],
ProtoTransfer: Cross-Modal Prototype Transfer for Point Cloud Segmentation,
ICCV23(3314-3324)
IEEE DOI 2401
BibRef

Onghena, P.[Pierre], Gigli, L.[Leonardo], Velasco-Forero, S.[Santiago],
Rotation-invariant Hierarchical Segmentation on Poincaré Ball for 3D Point Cloud,
SHARP23(1757-1766)
IEEE DOI 2401
BibRef

Hui, L.[Le], Tang, L.[Linghua], Dai, Y.C.[Yu-Chao], Xie, J.[Jin], Yang, J.[Jian],
Efficient LiDAR Point Cloud Oversegmentation Network,
ICCV23(17957-17966)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yang, C.K.[Cheng-Kun], Chen, M.H.[Min-Hung], Chuang, Y.Y.[Yung-Yu], Lin, Y.Y.[Yen-Yu],
2D-3D Interlaced Transformer for Point Cloud Segmentation with Scene-Level Supervision,
ICCV23(977-987)
IEEE DOI Code:
WWW Link. 2401
BibRef

Kong, L.D.[Ling-Dong], Liu, Y.Q.[You-Quan], Chen, R.[Runnan], Ma, Y.X.[Yue-Xin], Zhu, X.G.[Xin-Ge], Li, Y.[Yikang], Hou, Y.N.[Yue-Nan], Qiao, Y.[Yu], Liu, Z.W.[Zi-Wei],
Rethinking Range View Representation for LiDAR Segmentation,
ICCV23(228-240)
IEEE DOI 2401
BibRef

Liu, Y.Q.[You-Quan], Chen, R.[Runnan], Li, X.[Xin], Kong, L.[Lingdong], Yang, Y.C.[Yu-Chen], Xia, Z.Y.[Zhao-Yang], Bai, Y.Q.[Ye-Qi], Zhu, X.G.[Xin-Ge], Ma, Y.X.[Yue-Xin], Li, Y.[Yikang], Qiao, Y.[Yu], Hou, Y.N.[Yue-Nan],
UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase,
ICCV23(21605-21616)
IEEE DOI Code:
WWW Link. 2401
BibRef

Lu, Y.H.[Yu-Hang], Jiang, Q.[Qi], Chen, R.[Runnan], Hou, Y.N.[Yue-Nan], Zhu, X.G.[Xin-Ge], Ma, Y.X.[Yue-Xin],
See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data,
ICCV23(21617-21627)
IEEE DOI 2401
BibRef

Reichardt, L.[Laurenz], Ebert, N.[Nikolas], Wasenmüller, O.[Oliver],
360° from a Single Camera: A Few-Shot Approach for LiDAR Segmentation,
LIMIT23(1067-1075)
IEEE DOI 2401
BibRef

Li, P.[Pufan], Gao, X.[Xiang], Hu, Q.J.[Qian-Jiang], Hu, W.[Wei],
Robust Graph-Based Segmentation of Noisy Point Clouds,
ICIP23(3090-3094)
IEEE DOI 2312
BibRef

Chen, Y.H.[Yu-Hao], Gunraj, H.[Hayden], Zeng, E. .Z.X.[E. Zhi-Xuan], Meyer, R.[Robbie], Gilles, M.[Maximilian], Wong, A.[Alexander],
MMRNet: Improving Reliability for Multimodal Object Detection and Segmentation for Bin Picking via Multimodal Redundancy,
FaDE-TCV23(68-77)
IEEE DOI 2309
BibRef

Schön, R.[Robin], Ludwig, K.[Katja], Lienhart, R.[Rainer],
Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance,
L3D-IVU23(4809-4819)
IEEE DOI 2309
BibRef

Zhang, N.[Nan], Pan, Z.Y.[Zhi-Yi], Li, T.H.[Thomas H.], Gao, W.[Wei], Li, G.[Ge],
Improving Graph Representation for Point Cloud Segmentation via Attentive Filtering,
CVPR23(1244-1254)
IEEE DOI 2309
BibRef

Li, G.R.[Guang-Rui], Kang, G.L.[Guo-Liang], Wang, X.H.[Xiao-Han], Wei, Y.C.[Yun-Chao], Yang, Y.[Yi],
Adversarially Masking Synthetic to Mimic Real: Adaptive Noise Injection for Point Cloud Segmentation Adaptation,
CVPR23(20464-20474)
IEEE DOI 2309
BibRef

Rajendran, V.[Vickram], Tang, C.[Chuck], van Paasschen, F.[Frits],
Improving Rare Classes on nuScenes LiDAR segmentation Through Targeted Domain Adaptation,
WAD23(130-139)
IEEE DOI 2309
BibRef

Wu, C.Z.[Cheng-Zhi], Bi, X.[Xuelei], Pfrommer, J.[Julius], Cebulla, A.[Alexander], Mangold, S.[Simon], Beyerer, J.[Jürgen],
Sim2real Transfer Learning for Point Cloud Segmentation: An Industrial Application Case on Autonomous Disassembly,
WACV23(4520-4529)
IEEE DOI 2302
Point cloud compression, Learning systems, Service robots, Transfer learning, Pipelines, Data models, Applications: Robotics BibRef

Loiseau, R.[Romain], Aubry, M.[Mathieu], Landrieu, L.[Loïc],
Online Segmentation of LiDAR Sequences: Dataset and Algorithm,
ECCV22(XXXVIII:301-317).
Springer DOI 2211
BibRef

Sharma, G.[Gopal], Yin, K.X.[Kang-Xue], Maji, S.[Subhransu], Kalogerakis, E.[Evangelos], Litany, O.[Or], Fidler, S.[Sanja],
MvDeCor: Multi-view Dense Correspondence Learning for Fine-Grained 3D Segmentation,
ECCV22(II:550-567).
Springer DOI 2211
BibRef

Yang, P.[Pei], Wang, H.[Huan],
Regional Saliency Map Attack for Medical Image Segmentation,
ICIP22(846-850)
IEEE DOI 2211
Training, Measurement, Image segmentation, Visualization, Perturbation methods, Semantics, Neural networks, Index Terms, medical image segmentation BibRef

Ye, M.S.[Mao-Sheng], Wan, R.[Rui], Xu, S.J.[Shuang-Jie], Cao, T.[Tongyi], Chen, Q.F.[Qi-Feng],
Efficient Point Cloud Segmentation with Geometry-Aware Sparse Networks,
ECCV22(XXIX:196-212).
Springer DOI 2211
BibRef

Yang, C.K.[Cheng-Kun], Wu, J.J.[Ji-Jia], Chen, K.S.[Kai-Syun], Chuang, Y.Y.[Yung-Yu], Lin, Y.Y.[Yen-Yu],
An MIL-Derived Transformer for Weakly Supervised Point Cloud Segmentation,
CVPR22(11820-11829)
IEEE DOI 2210
Point cloud compression, Adaptation models, Image segmentation, Image recognition, Semantics, Transformers, Segmentation, Efficient learning and inferences BibRef

Wang, X.L.[Xin-Long], Yu, Z.D.[Zhi-Ding], de Mello, S.[Shalini], Kautz, J.[Jan], Anandkumar, A.[Anima], Shen, C.H.[Chun-Hua], Alvarez, J.M.[Jose M.],
FreeSOLO: Learning to Segment Objects without Annotations,
CVPR22(14156-14166)
IEEE DOI 2210
Location awareness, Image segmentation, Image recognition, Annotations, Manuals, Recognition: detection, Self- semi- meta- unsupervised learning BibRef

Liu, L.[Leyao], Zheng, T.[Tian], Lin, Y.J.[Yun-Jou], Ni, K.[Kai], Fang, L.[Lu],
INS-Conv: Incremental Sparse Convolution for Online 3D Segmentation,
CVPR22(18953-18962)
IEEE DOI 2210
Performance evaluation, Uncertainty, Convolution, Shape, Semantics, Pipelines, grouping and shape analysis, retrieval, Segmentation, Recognition: detection BibRef

Nie, D.[Dong], Lan, R.[Rui], Wang, L.[Ling], Ren, X.F.[Xiao-Feng],
Pyramid Architecture for Multi-Scale Processing in Point Cloud Segmentation,
CVPR22(17263-17273)
IEEE DOI 2210
Point cloud compression, Representation learning, Image segmentation, Fuses, Semantics, grouping and shape analysis BibRef

Tang, L.[Liyao], Zhan, Y.B.[Yi-Bing], Chen, Z.[Zhe], Yu, B.S.[Bao-Sheng], Tao, D.C.[Da-Cheng],
Contrastive Boundary Learning for Point Cloud Segmentation,
CVPR22(8479-8489)
IEEE DOI 2210
Point cloud compression, Measurement, Codes, Computational modeling, Scene analysis and understanding BibRef

Lai, X.[Xin], Liu, J.H.[Jian-Hui], Jiang, L.[Li], Wang, L.W.[Li-Wei], Zhao, H.S.[Heng-Shuang], Liu, S.[Shu], Qi, X.J.[Xiao-Juan], Jia, J.Y.[Jia-Ya],
Stratified Transformer for 3D Point Cloud Segmentation,
CVPR22(8490-8499)
IEEE DOI 2210
Point cloud compression, Transformers, Encoding, Computational efficiency, grouping and shape analysis BibRef

Nie, X.[Xing], Liu, Y.C.[Yong-Cheng], Chen, S.H.[Shao-Hong], Chang, J.L.[Jian-Long], Huo, C.L.[Chun-Lei], Meng, G.F.[Gao-Feng], Tian, Q.[Qi], Hu, W.M.[Wei-Ming], Pan, C.H.[Chun-Hong],
Differentiable Convolution Search for Point Cloud Processing,
ICCV21(7417-7426)
IEEE DOI 2203
To enable CNN. Point cloud compression, Directed acyclic graph, Convolution, Shape, Heuristic algorithms, Segmentation, Representation learning BibRef

Lê, E.T.[Eric-Tuan], Sung, M.[Minhyuk], Ceylan, D.[Duygu], Mech, R.[Radomir], Boubekeur, T.[Tamy], Mitra, N.J.[Niloy J.],
CPFN: Cascaded Primitive Fitting Networks for High-Resolution Point Clouds,
ICCV21(7438-7446)
IEEE DOI 2203
Point cloud compression, Codes, Fitting, Merging, Reverse engineering, Pipelines, Segmentation, grouping and shape, BibRef

Hui, L.[Le], Yuan, J.[Jia], Cheng, M.[Mingmei], Xie, J.[Jin], Zhang, X.Y.[Xiao-Ya], Yang, J.[Jian],
Superpoint Network for Point Cloud Oversegmentation,
ICCV21(5490-5499)
IEEE DOI 2203
Point cloud compression, Codes, Semantics, Stereo, 3D from multiview and other sensors, BibRef

Yan, S.M.[Si-Ming], Yang, Z.P.[Zhen-Pei], Ma, C.Y.[Chong-Yang], Huang, H.B.[Hai-Bin], Vouga, E.[Etienne], Huang, Q.X.[Qi-Xing],
HPNet: Deep Primitive Segmentation Using Hybrid Representations,
ICCV21(2733-2742)
IEEE DOI 2203
Point cloud compression, Shape, Semantics, Performance gain, Benchmark testing, Detection and localization in 2D and 3D, grouping and shape BibRef

Xu, J.Y.[Jian-Yun], Zhang, R.X.[Rui-Xiang], Dou, J.[Jian], Zhu, Y.S.[Yu-Shi], Sun, J.[Jie], Pu, S.L.[Shi-Liang],
RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentation,
ICCV21(16004-16013)
IEEE DOI 2203
Point cloud compression, Quantization (signal), Laser radar, Image resolution, Logic gates, Solids, 3D from multiview and other sensors BibRef

Yang, C.K.[Cheng-Kun], Chuang, Y.Y.[Yung-Yu], Lin, Y.Y.[Yen-Yu],
Unsupervised Point Cloud Object Co-segmentation by Co-contrastive Learning and Mutual Attention Sampling,
ICCV21(7315-7324)
IEEE DOI 2203
Point cloud compression, Deep learning, Correlation, Annotations, Neural networks, Segmentation, grouping and shape, 3D from multiview and other sensors BibRef

Ye, M.S.[Mao-Sheng], Xu, S.J.[Shuang-Jie], Cao, T.Y.[Tong-Yi], Chen, Q.F.[Qi-Feng],
DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation,
ICCV21(7427-7436)
IEEE DOI 2203
Point cloud compression, Representation learning, Degradation, Runtime, Costs, Feature extraction, Segmentation, grouping and shape, Vision for robotics and autonomous vehicles BibRef

Wei, Y.M.[Yi-Min], Liu, H.[Hao], Xie, T.T.[Ting-Ting], Ke, Q.H.[Qiu-Hong], Guo, Y.L.[Yu-Lan],
Spatial-Temporal Transformer for 3D Point Cloud Sequences,
WACV22(657-666)
IEEE DOI 2202
Point cloud compression, Solid modeling, Aggregates, Semantics, Grouping and Shape BibRef

Shakibajahromi, B.[Bahareh], Shayestehmanesh, S.[Saeed], Schwartz, D.[Daniel], Shokoufandeh, A.[Ali],
HyNet: 3D Segmentation Using Hybrid Graph Networks,
3DV21(805-814)
IEEE DOI 2201
Representation learning, Deep learning, Solid modeling, Shape, Biological system modeling, Focusing BibRef

Fan, S.Q.[Si-Qi], Dong, Q.L.[Qiu-Lei], Zhu, F.[Fenghua], Lv, Y.S.[Yi-Sheng], Ye, P.J.[Pei-Jun], Wang, F.Y.[Fei-Yue],
SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation,
CVPR21(14499-14508)
IEEE DOI 2111
Semantics, Network architecture BibRef

Tian, H.[Hao], Chen, Y.T.[Yun-Tao], Dai, J.F.[Ji-Feng], Zhang, Z.X.[Zhao-Xiang], Zhu, X.[Xizhou],
Unsupervised Object Detection with LiDAR Clues,
CVPR21(5958-5968)
IEEE DOI 2111
Training, Location awareness, Image segmentation, Laser radar, Annotations, Object detection BibRef

Aguilar, C.[Camilo], Comer, M.[Mary], Hanhan, I.[Imad], Agyei, R.[Ronald], Sangid, M.[Michael],
3D Fiber Segmentation with Deep Center Regression and Geometric Clustering,
CVMI21(3741-3749)
IEEE DOI 2109

WWW Link. Geometry, Training, Image color analysis, Shape, Microscopy, Neural networks BibRef

Pan, Y.[Yunyi], Gan, Y.[Yuan], Liu, K.[Kun], Zhang, Y.[Yan],
Progressive Scene Segmentation Based on Self-Attention Mechanism,
ICPR21(3985-3992)
IEEE DOI 2105
Convolution, Semantics, Benchmark testing, Decoding, Task analysis, 3D Scene Understanding BibRef

Krispel, G., Opitz, M., Waltner, G., Possegger, H., Bischof, H.,
FuseSeg: LiDAR Point Cloud Segmentation Fusing Multi-Modal Data,
WACV20(1863-1872)
IEEE DOI 2006
Laser radar, Task analysis, Sensors, Laser beams, Fuses, Image segmentation BibRef

Barrile, V., Candela, G., Fotia, A.,
Point Cloud Segmentation Using Image Processing Techniques For Structural Analysis,
GEORES19(187-193).
DOI Link 1912
BibRef

Sharma, G.[Gopal], Liu, D.[Difan], Maji, S.[Subhransu], Kalogerakis, E.[Evangelos], Chaudhuri, S.[Siddhartha], Mech, R.[Radomír],
Parsenet: A Parametric Surface Fitting Network for 3d Point Clouds,
ECCV20(VII:261-276).
Springer DOI 2011
BibRef

Zheng, T., Chen, C., Yuan, J., Li, B., Ren, K.,
PointCloud Saliency Maps,
ICCV19(1598-1606)
IEEE DOI 2004
Code, Saliency.
WWW Link. convolutional neural nets, image classification, image representation, image segmentation, object detection, DGCNN, Predictive models BibRef

Zhang, Z.Y.[Zhi-Yuan], Hua, B.S.[Binh-Son], Yeung, S.K.[Sai-Kit],
ShellNet: Efficient Point Cloud Convolutional Neural Networks Using Concentric Shells Statistics,
ICCV19(1607-1616)
IEEE DOI 2004
convolutional neural nets, feature extraction, image classification, image representation, image segmentation, Semantics BibRef

Honma, R., Date, H., Kanai, S.,
MLS Point Cloud Segmentation Based On Feature Points of Scanlines,
Laser19(1007-1013).
DOI Link 1912
BibRef

Zhong, Z., Zhang, C., Liu, Y., Wu, Y.,
VIASEG: Visual Information Assisted Lightweight Point Cloud Segmentation,
ICIP19(1500-1504)
IEEE DOI 1910
Point Cloud Segmentation, Cross-modality Fusion, Fully Convolutional Residual Network BibRef

Walczak, J.[Jakub], Wojciechowski, A.[Adam],
Clustering Quality Measures for Point Cloud Segmentation Tasks,
ICCVG18(173-186).
Springer DOI 1810
BibRef

Kuçak, R.A., Özdemir, E., Erol, S.,
The Segmentation of Point Clouds with K-means and ANN (Artifical Neural Network),
Hannover17(595-598).
DOI Link 1805
BibRef

Lam, J.[Joseph], Greenspan, M.[Michael],
On the Repeatability of 3D Point Cloud Segmentation Based on Interest Points,
CRV12(9-16).
IEEE DOI 1207
BibRef

Akman, O.[Oytun], Bayramoglu, N.[Neslihan], Alatan, A.A.[A. Aydin], Jonker, P.P.[Pieter P.],
Utilization of spatial information for point cloud segmentation,
3DTV10(1-4).
IEEE DOI 1006
BibRef

Sedlacek, D.[David], Zara, J.[Jiri],
Graph Cut Based Point-Cloud Segmentation for Polygonal Reconstruction,
ISVC09(II: 218-227).
Springer DOI 0911
BibRef

Zhan, Q.M.[Qing-Ming], Liang, Y.B.[Yu-Bin], Xiao, Y.H.[Ying-Hui],
Color-Based Segmentation of Point Clouds,
Laser09(248). 0909
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Range and Color, RGB-D Segmentation and Analysis .


Last update:Jan 20, 2025 at 11:36:25