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.
See also Semantic Object Detection, 3D, Depth.

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

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

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

Li, D.[Dawei], Shi, G.L.[Guo-Liang], Wu, Y.[Yuhao], Yang, Y.[Yanping], 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


Xiao, C.X.[Chen-Xi], Wachs, J.[Juan],
Triangle-Net: Towards Robustness in Point Cloud Learning,
WACV21(826-835)
IEEE DOI 2106
Service robots, Surveillance, Neural networks, Feature extraction, Robustness BibRef

Qiu, S.[Shi], Anwar, S.[Saeed], Barnes, N.[Nick],
Dense-Resolution Network for Point Cloud Classification and Segmentation,
WACV21(3812-3821)
IEEE DOI 2106
Training, Visualization, Adaptation models, Computational modeling BibRef

Yang, Y.R.[Yi-Rong], Fan, B.[Bin], Liu, Y.C.[Yong-Cheng], Lin, H.[Hua], Zhang, J.Y.[Ji-Yong], Liu, X.[Xin], Cai, X.Y.[Xin-Yu], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
Deep Space Probing for Point Cloud Analysis,
ICPR21(10235-10242)
IEEE DOI 2105
Geometry, Convolution, Neural networks, Benchmark testing, Convolutional neural networks BibRef

Lin, H.[Hua], Fan, B.[Bin], Liu, Y.C.[Yong-Cheng], Yang, Y.R.[Yi-Rong], Pan, Z.[Zheng], Shi, J.B.[Jian-Bo], Pan, C.H.[Chun-Hong], Xie, H.W.[Hui-Wen],
PointSpherical: Deep Shape Context for Point Cloud Learning in Spherical Coordinates,
ICPR21(10266-10273)
IEEE DOI 2105
Solid modeling, Shape, Convolution, Semantics, Feature extraction BibRef

Alliegro, A.[Antonio], Boscaini, D.[Davide], Tommasi, T.[Tatiana],
Joint Supervised and Self-Supervised Learning for 3D Real World Challenges,
ICPR21(6718-6725)
IEEE DOI 2105
Solid modeling, Shape, Transfer learning, Supervised learning, Intelligent agents 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

Zhong, M.[Min], Zeng, G.[Gang],
Enhanced Vote Network for 3D Object Detection in Point Clouds,
ICPR21(6624-6631)
IEEE DOI 2105
Aggregates, Face recognition, Semantics, Object detection, Benchmark testing, Feature extraction 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

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

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

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

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

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
Depth Object Detection, 3D Object Detection .


Last update:Jul 11, 2021 at 20:18:24