11.2.4.1 Depth Object Segmentation, Point Cloud Segmentation

Chapter Contents (Back)
Object Detection. Segmentation, Range. Object Segmentation. Point Cloud Segmentation. Segment the objects. More particularily:
See also Range and Color, RGB-D Segmentation and Analysis.
See also Depth Object Detection, 3D Object Detection.

Zhang, J.X.[Ji-Xian], Lin, X.G.[Xiang-Guo],
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],
Graph based over-segmentation methods for 3D point clouds,
CVIU(174), 2018, pp. 12-23.
Elsevier DOI 1812
3D point cloud over-segmentation, 3D point cloud segmentation, Super-points, Grouping BibRef

Poux, F.[Florent], Billen, R.[Roland],
Voxel-based 3D Point Cloud Semantic Segmentation: Unsupervised Geometric and Relationship Featuring vs Deep Learning Methods,
IJGI(8), No. 5, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Li, Y., Ma, L., Zhong, Z., Cao, D., Li, J.,
TGNet: Geometric Graph CNN on 3-D Point Cloud Segmentation,
GeoRS(58), No. 5, May 2020, pp. 3588-3600.
IEEE DOI 2005
Feature extraction, Convolution, Semantics, Kernel, Correlation, Task analysis, Deep learning, semantic segmentation 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

Feng, M.T.[Ming-Tao], Gilani, S.Z.[Syed Zulqarnain], Wang, Y.N.[Yao-Nan], Zhang, L.[Liang], Mian, A.[Ajmal],
Relation Graph Network for 3D Object Detection in Point Clouds,
IP(30), 2021, pp. 92-107.
IEEE DOI 2011
Proposals, Object detection, Feature extraction, Laser radar, deep learning BibRef

Lei, H.[Huan], Akhtar, N.[Naveed], Mian, A.[Ajmal],
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, Convolutional codes, Integrated circuits, Robustness, Computer architecture BibRef

Hsu, P.H.[Pai-Hui], Zhuang, Z.Y.[Zong-Yi],
Incorporating Handcrafted Features into Deep Learning for Point Cloud Classification,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Li, X.[Xiaohan], 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

Tian, Y.F.[Yi-Fei], Chen, L.[Long], Song, W.[Wei], Sung, Y.S.[Yun-Sick], Woo, S.C.[Sang-Chul],
DGCB-Net: Dynamic Graph Convolutional Broad Network for 3D Object Recognition in Point Cloud,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Su, F.[Fei], Zhu, H.H.[Hai-Hong], Chen, T.Y.[Tao-Yi], Li, L.[Lin], Yang, F.[Fan], Peng, H.X.[Hui-Xiang], Tang, L.[Lei], Zuo, X.K.[Xin-Kai], Liang, Y.F.[Yi-Fan], Ying, S.[Shen],
An anchor-based graph method for detecting and classifying indoor objects from cluttered 3D point clouds,
PandRS(172), 2021, pp. 114-131.
Elsevier DOI 2101
Point cloud, Object classification, Functional part, Graph matching, Super-graph, Graph similarity BibRef

Wang, W.M.[Wei-Ming], You, Y.[Yang], Liu, W.[Wenhai], Lu, C.[Cewu],
Point cloud classification with deep normalized Reeb graph convolution,
IVC(106), 2021, pp. 104092.
Elsevier DOI 2102
Reeb graph, Point cloud, Graph normalization 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, G.Y.[Gong-Yang], Liu, Z.[Zhi], Chen, M.Y.[Min-Yu], Bai, Z.[Zhen], Lin, W.S.[Wei-Si], Ling, H.B.[Hai-Bin],
Hierarchical Alternate Interaction Network for RGB-D Salient Object Detection,
IP(30), 2021, pp. 3528-3542.
IEEE DOI 2103
Object detection, Feature extraction, Color, Visualization, Task analysis, Computer architecture, Stereo image processing, alternate interaction BibRef

Li, G.Y.[Gong-Yang], Liu, Z.[Zhi], Ye, L.W.[Lin-Wei], Wang, Y.[Yang], Ling, H.B.[Hai-Bin],
Cross-modal Weighting Network for RGB-D Salient Object Detection,
ECCV20(XVII:665-681).
Springer DOI 2011
BibRef

Zhang, X. .L.[Xin- Liang], Fu, C.L.[Chen-Lin], Zhao, Y.J.[Yun-Ji], Xu, X.Z.[Xiao-Zhuo],
Hybrid feature CNN model for point cloud classification and segmentation,
IET-IPR(14), No. 16, 19 December 2020, pp. 4086-4091.
DOI Link 2103
BibRef

Gao, Q.[Qian], Shen, X.[Xukun],
ThickSeg: Efficient semantic segmentation of large-scale 3D point clouds using multi-layer projection,
IVC(108), 2021, pp. 104161.
Elsevier DOI 2104
3D point cloud, Semantic segmentation, Convolutional neural network, Large scale BibRef

Kwak, J.[Jeonghoon], Sung, Y.[Yunsick],
DeepLabV3-Refiner-Based Semantic Segmentation Model for Dense 3D Point Clouds,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Wang, Q.[Qi], Chen, J.[Jian], Deng, J.Q.[Jian-Qiang], Zhang, X.F.[Xin-Fang],
3D-CenterNet: 3D object detection network for point clouds with center estimation priority,
PR(115), 2021, pp. 107884.
Elsevier DOI 2104
3D object detection, Point cloud, Deep learning BibRef

Ponciano, J.J.[Jean-Jacques], Roetner, M.[Moritz], Reiterer, A.[Alexander], Boochs, F.[Frank],
Object Semantic Segmentation in Point Clouds: Comparison of a Deep Learning and a Knowledge-Based Method,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef


Demilew, S.S.[Selameab S.], Aghdam, H.H.[Hamed H.], Laganičre, R.[Robert], Petriu, E.M.[Emil M.],
FA3D: Fast and Accurate 3d Object Detection,
ISVC20(I:397-409).
Springer DOI 2103
BibRef

Krishna, O.[Onkar], Irie, G.[Go], Wu, X.[Xiaomeng], Kawanishi, T.[Takahito], Kashino, K.[Kunio],
Adaptive Spotting: Deep Reinforcement Object Search in 3d Point Clouds,
ACCV20(III:257-272).
Springer DOI 2103
BibRef

Sun, W.X.[Wei-Xuan], Zhang, J.[Jing], Barnes, N.[Nick],
3D Guided Weakly Supervised Semantic Segmentation,
ACCV20(I:585-602).
Springer DOI 2103
BibRef

Wu, G.N.[Guang-Nan], Pan, Z.Y.[Zhi-Yi], Jiang, P.[Peng], Tu, C.H.[Chang-He],
Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds,
ACCV20(I:209-226).
Springer DOI 2103
BibRef

Kölle, M.[Michael], Walter, V.[Volker], Schmohl, S.[Stefan], Soergel, U.[Uwe],
Remembering Both the Machine and the Crowd When Sampling Points: Active Learning for Semantic Segmentation of ALS Point Clouds,
PRRS20 (505-520).
Springer DOI 2103
BibRef

Cortinhal, T.[Tiago], Tzelepis, G.[George], Aksoy, E.E.[Eren Erdal],
Salsanext: Fast, Uncertainty-aware Semantic Segmentation of Lidar Point Clouds,
ISVC20(II:207-222).
Springer DOI 2103
BibRef

Zhang, Y.[Yi], Ye, Y.[Yuwen], Xiang, Z.[Zhiyu], Gu, J.[Jiaqi],
Sdp-net: Scene Flow Based Real-time Object Detection and Prediction from Sequential 3d Point Clouds,
ACCV20(I:140-157).
Springer DOI 2103
BibRef

Akadas, K.[Kiran], Gangisetty, S.[Shankar],
3d Semantic Segmentation for Large-scale Scene Understanding,
MLCSA20(87-102).
Springer DOI 2103
BibRef

Wang, X., Fan, X., Zhao, D.,
A semantic labeling framework for ALS point clouds based on discretization and CNN,
VCIP20(58-61)
IEEE DOI 2102
Semantics, Labeling, Entropy, Neural networks, Microprocessors, Computer architecture, CNN BibRef

Liu, X., Cao, J., Bi, Q., Wang, J., Shi, B., Wei, Y.,
Dense Point Diffusion for 3D Object Detection,
3DV20(762-770)
IEEE DOI 2102
Convolution, Object detection, Feature extraction, Task analysis, Quantization (signal) BibRef

Saltori, C., Lathuiličre, S., Sebe, N., Ricci, E., Galasso, F.,
SF-UDA3D: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection,
3DV20(771-780)
IEEE DOI 2102
Annotations, Detectors, Adaptation models, Laser radar, Target tracking, LiDAR data BibRef

Duerr, F., Pfaller, M., Weigel, H., Beyerer, J.,
LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory Alignment,
3DV20(781-790)
IEEE DOI 2102
Image segmentation, Feature extraction, Semantics, Sensors, Laser radar, Task analysis, Point clouds BibRef

Yu, M., Liu, J., Ni, B., Li, C.,
Two-Stage Relation Constraint for Semantic Segmentation of Point Clouds,
3DV20(271-280)
IEEE DOI 2102
Semantics, Task analysis, Convolution, Computer architecture, Heuristic algorithms, Training, Semantic Segmentation BibRef

Widyaningrum, E., Fajari, M.K., Lindenbergh, R.C., Hahn, M.,
Tailored Features for Semantic Segmentation with A DGCNN Using Free Training Samples of A Colored Airborne Point Cloud,
ISPRS20(B2:339-346).
DOI Link 2012
BibRef

Leichter, A., Werner, M., Sester, M.,
Feature-Extraction from All-scale Neighborhoods with Applications To Semantic Segmentation of Point Clouds,
ISPRS20(B2:263-270).
DOI Link 2012
BibRef

Zhang, F.H.[Fei-Hu], Fang, J.[Jin], Wah, B.[Benjamin], Torr, P.[Philip],
Deep Fusionnet for Point Cloud Semantic Segmentation,
ECCV20(XXIV:644-663).
Springer DOI 2012
BibRef

He, T.[Tong], Gong, D.[Dong], Tian, Z.[Zhi], Shen, C.H.[Chun-Hua],
Learning and Memorizing Representative Prototypes for 3d Point Cloud Semantic and Instance Segmentation,
ECCV20(XVIII:564-580).
Springer DOI 2012
BibRef

Liu, J.X.[Jin-Xian], Yu, M.H.[Ming-Hui], Ni, B.B.[Bing-Bing], Chen, Y.[Ye],
Self-prediction for Joint Instance and Semantic Segmentation of Point Clouds,
ECCV20(XXII:187-204).
Springer DOI 2011
BibRef

Wong, C.C.[Chi-Chong], Vong, C.M.[Chi-Man],
Efficient Outdoor 3d Point Cloud Semantic Segmentation for Critical Road Objects and Distributed Contexts,
ECCV20(XXVII:499-514).
Springer DOI 2011
BibRef

Du, A.[Anan], Pang, S.C.[Shu-Chao], Huang, X.S.[Xiao-Shui], Zhang, J.[Jian], Wu, Q.A.[Qi-Ang],
Exploring Long-Short-Term Context For Point Cloud Semantic Segmentation,
ICIP20(2755-2759)
IEEE DOI 2011
Task analysis, Semantics, Decoding, Feature extraction, Context modeling, Training, point cloud, long-short-term context BibRef

Xu, X., Lee, G.H.,
Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels,
CVPR20(13703-13712)
IEEE DOI 2008
Task analysis, Image color analysis, Training, Shape, Semantics, Labeling 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

Wang, L.[Lei], Huang, Y.[Yuchun], Hou, Y.[Yaolin], Zhang, S.[Shenman], Shan, J.[Jie],
Graph Attention Convolution for Point Cloud Semantic Segmentation,
CVPR19(10288-10297).
IEEE DOI 2002
BibRef

Adam, A., Grammatikopoulos, L., Karras, G., Protopapadakis, E., Karantzalos, K.,
A Semantic 3d Point Cloud Segmentation Approach Based On Optimal View Selection for 2d Image Feature Extraction,
LC3D19(9-14).
DOI Link 1912
BibRef

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

Hu, Q.Y.[Qing-Yong], Yang, B.[Bo], Xie, L.H.[Lin-Hai], Rosa, S.[Stefano], Guo, Y.L.[Yu-Lan], Wang, Z.H.[Zhi-Hua], Trigoni, N.[Niki], Markham, A.[Andrew],
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds,
CVPR20(11105-11114)
IEEE DOI 2008
Semantics, Feature extraction, Task analysis, Encoding, Computer architecture, Benchmark testing BibRef

Ma, Y.X.[Yan-Xin], Guo, Y.L.[Yu-Lan], Lei, Y.J.[Yin-Jie], Lu, M.[Min], Zhang, J.[Jun],
3DMAX-Net: A Multi-Scale Spatial Contextual Network for 3D Point Cloud Semantic Segmentation,
ICPR18(1560-1566)
IEEE DOI 1812
Feature extraction, Semantics, Labeling, Neural networks, Task analysis BibRef

Landrieu, L., Simonovsky, M.,
Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs,
CVPR18(4558-4567)
IEEE DOI 1812
Shape, Semantics, Image segmentation, Image edge detection, Pipelines BibRef

Wang, W., Yu, R., Huang, Q., Neumann, U.,
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation,
CVPR18(2569-2578)
IEEE DOI 1812
Proposals, Image segmentation, Semantics, Feature extraction 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

Biasutti, P., Lepetit, V., Aujol, J., Brédif, M., Bugeau, A.,
LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net,
CVRSUAD19(942-950)
IEEE DOI 2004
feature extraction, graphics processing units, image segmentation, optical radar, radar imaging, LU-Net, deep learning BibRef

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

Jiang, L., Zhao, H., Liu, S., Shen, X., Fu, C., Jia, J.,
Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation,
ICCV19(10432-10440)
IEEE DOI 2004
graph theory, image colour analysis, image segmentation, message passing, object detection, Labeling 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
Depth Object Detection, 3D Object Detection .


Last update:May 10, 2021 at 18:51:10