11.2.4.7 Semantic Object Detection, 3D, Depth

Chapter Contents (Back)
Semantic Segmentation. Object Detection. Semantic Object Detection.

Thonnat, M.,
Semantic Interpretation of 3-D Stereo Data: Finding the Main Structures,
PRAI(2), 1988, pp. 509-525. BibRef 8800
Earlier: ICPR86(1051-1054). BibRef

Ma, R., Thonnat, M.,
Object Detection in Outdoor Scenes by Disparity Map Segmentation,
ICPR92(I:546-549).
IEEE DOI BibRef 9200

Boochs, F.[Frank], Kern, F.[Fredie], Schütze, R.[Rainer], Marbs, A.[Andreas],
Approaches for geometrical and semantic modelling of huge unstructured 3D point clouds,
PFG(2009), No. 1, 2009, pp. 65-77.
WWW Link. 1211
BibRef

Su, W.[Wen], Wang, Z.F.[Zeng-Fu],
Widening residual skipped network for semantic segmentation,
IET-IPR(11), No. 10, October 2017, pp. 880-887.
DOI Link 1710
BibRef
Earlier:
Regularized fully convolutional networks for RGB-D semantic segmentation,
VCIP16(1-4)
IEEE DOI 1701
Brightness BibRef

Pagnutti, G.[Giampaolo], Minto, L.[Ludovico], Zanuttigh, P.[Pietro],
Segmentation and semantic labelling of RGBD data with convolutional neural networks and surface fitting,
IET-CV(11), No. 8, December 2017, pp. 633-642.
DOI Link 1712
BibRef

Guo, Y.R.[Yan-Rong], Chen, T.[Tao],
Semantic segmentation of RGBD images based on deep depth regression,
PRL(109), 2018, pp. 55-64.
Elsevier DOI 1806
Deep depth regression, RGBD semantic segmentation, Convolutional neural network, Fully convolutional network BibRef

Sun, Y.[Ying], Zhang, X.C.[Xin-Chang], Xin, Q.C.[Qin-Chuan], Huang, J.F.[Jian-Feng],
Developing a multi-filter convolutional neural network for semantic segmentation using high-resolution aerial imagery and LiDAR data,
PandRS(143), 2018, pp. 3-14.
Elsevier DOI 1808
LiDAR, High-resolution imagery, Multi-modal fusion, Multi-resolution segmentation, Semantic segmentation BibRef

Ponciano, J.J.[Jean-Jacques], Trémeau, A.[Alain], Boochs, F.[Frank],
Automatic Detection of Objects in 3D Point Clouds Based on Exclusively Semantic Guided Processes,
IJGI(8), No. 10, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Boochs, F.[Frank], Karmacharya, A., Marbs, A.,
Knowledge-based Object Detection In Laser Scanning Point Clouds,
ISPRS12(XXXIX-B3:91-96).
DOI Link 1209
BibRef

Truong, H.Q.[Hung Quoc], Ben Hmida, H.[Helmi], Marbs, A.[Andreas], Boochs, F.[Frank],
Integration of knowledge into the detection of objects in point clouds,
PCVIA10(B:143).
PDF File. 1009
BibRef

Aytaylan, H.[Hakan], Yuksel, S.E.[Seniha Esen],
Fully-connected semantic segmentation of hyperspectral and LiDAR data,
IET-CV(13), No. 3, April 2019, pp. 285-293.
DOI Link 1904
BibRef

Ge, X.M.[Xu-Ming], Wu, B.[Bo], Li, Y.[Yuan], Hu, H.[Han],
A Multi-Primitive-Based Hierarchical Optimal Approach for Semantic Labeling of ALS Point Clouds,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Li, Y.[Yong], Chen, D.[Dong], Du, X.[Xiance], Xia, S.B.[Shao-Bo], Wang, Y.L.[Yu-Liang], Xu, S.[Sheng], Yang, Q.A.[Qi-Ang],
Higher-Order Conditional Random Fields-Based 3D Semantic Labeling of Airborne Laser-Scanning Point Clouds,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Fang, H.[Hao], Lafarge, F.[Florent],
Pyramid scene parsing network in 3D: Improving semantic segmentation of point clouds with multi-scale contextual information,
PandRS(154), 2019, pp. 246-258.
Elsevier DOI 1907
Point cloud, Semantic segmentation, Deep learning, Multi-scale contextual information 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

Zhou, H.[Heng], Fang, Z.J.[Zhi-Jun], Gao, Y.B.[Yong-Bin], Huang, B.[Bo], Zhong, C.[Cengsi], Shang, R.X.[Ruo-Xi],
Feature fusion network based on attention mechanism for 3D semantic segmentation of point clouds,
PRL(133), 2020, pp. 327-333.
Elsevier DOI 2005
3D Semantic segmentation, Point clouds, Feature fusion, Attention mechanism BibRef

Lin, Y.P.[Ya-Ping], Vosselman, G.[George], Cao, Y.P.[Yan-Peng], Yang, M.Y.[Michael Ying],
Active and incremental learning for semantic ALS point cloud segmentation,
PandRS(169), 2020, pp. 73-92.
Elsevier DOI 2011
Point clouds, Semantic segmentation, Active learning, Incremental learning, Deep learning BibRef

Lin, D.[Di], Huang, H.[Hui],
Zig-Zag Network for Semantic Segmentation of RGB-D Images,
PAMI(42), No. 10, October 2020, pp. 2642-2655.
IEEE DOI 2009
Image segmentation, Semantics, Decoding, Image resolution, Feature extraction, Correlation, RGB-D images, convolutional neural networks BibRef

Lin, D.[Di], Chen, G.Y.[Guang-Yong], Cohen-Or, D.[Daniel], Heng, P.A.[Pheng-Ann], Huang, H.[Hui],
Cascaded Feature Network for Semantic Segmentation of RGB-D Images,
ICCV17(1320-1328)
IEEE DOI 1802
feature extraction, feedforward neural nets, image colour analysis, image representation, image segmentation, Visualization BibRef

Han, X.[Xu], Dong, Z.[Zhen], Yang, B.S.[Bi-Sheng],
A point-based deep learning network for semantic segmentation of MLS point clouds,
PandRS(175), 2021, pp. 199-214.
Elsevier DOI 2105
Point cloud, 3D deep learning, Semantic segmentation, Feature aggregation, Unbalanced classes BibRef

Jiang, B.[Bo], Zhou, Z.[Zitai], Wang, X.[Xiao], Tang, J.[Jin], Luo, B.[Bin],
cmSalGAN: RGB-D Salient Object Detection With Cross-View Generative Adversarial Networks,
MultMed(23), 2021, pp. 1343-1353.
IEEE DOI 2105
Saliency detection, Feature extraction, Object detection, Generative adversarial networks, Fuses, Multi-view Learning BibRef

Chen, L.Z., Lin, Z., Wang, Z., Yang, Y.L., Cheng, M.M.,
Spatial Information Guided Convolution for Real-Time RGBD Semantic Segmentation,
IP(30), 2021, pp. 2313-2324.
IEEE DOI 2102
convolutional neural nets, geometry, image colour analysis, image segmentation, stereo image processing, RGBD semantic segmentation BibRef

Zhang, G.D.[Guo-Dong], Xue, J.H.[Jing-Hao], Xie, P.W.[Peng-Wei], Yang, S.[Sifan], Wang, G.J.[Gui-Jin],
Non-Local Aggregation for RGB-D Semantic Segmentation,
SPLetters(28), 2021, pp. 658-662.
IEEE DOI 2104
Semantics, Feature extraction, Interpolation, Image segmentation, Benchmark testing, Training, RGB-D semantic segmentation 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

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

Shuai, H.[Hui], Xu, X.[Xiang], Liu, Q.S.[Qing-Shan],
Backward Attentive Fusing Network With Local Aggregation Classifier for 3D Point Cloud Semantic Segmentation,
IP(30), 2021, pp. 4973-4984.
IEEE DOI 2106
Semantics, Feature extraction, Decoding, Iron, Noise measurement, Aggregates, local aggregation classifier BibRef

Liu, W.[Wei], Luo, Z.M.[Zhi-Ming], Cai, Y.Z.[Yuan-Zheng], Yu, Y.[Ying], Ke, Y.[Yang], Junior, J.M.[José Marcato], Gonçalves, W.N.[Wesley Nunes], Li, J.[Jonathan],
Adversarial Unsupervised Domain Adaptation for 3D Semantic Segmentation with Multi-Modal Learning,
PandRS(176), 2021, pp. 211-221.
Elsevier DOI 2106
Semantic segmentation, Point cloud, Domain adaptation, Adversarial learning, Multi-modal learning BibRef

Lin, Y.P.[Ya-Ping], Vosselman, G.[George], Cao, Y.P.[Yan-Peng], Yang, M.Y.[Michael Ying],
Local and global encoder network for semantic segmentation of Airborne laser scanning point clouds,
PandRS(176), 2021, pp. 151-168.
Elsevier DOI 2106
Point clouds, Semantic segmentation, Global context, Attention models BibRef

Sithole, G.[George], Vosselman, G.[George],
Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds,
PandRS(59), No. 1-2, August 2004, pp. 85-101.
Elsevier DOI 0411

See also Bridge detection in airborne laser scanner data. BibRef

Lin, Y.P.[Ya-Ping], Vosselman, G.[George], Yang, M.Y.[Michael Ying],
Weakly supervised semantic segmentation of airborne laser scanning point clouds,
PandRS(187), 2022, pp. 79-100.
Elsevier DOI 2205
Airborne laser scanning, Point clouds, Weak supervision, Semantic segmentation, Subcloud labels BibRef

Xiao, A.[Aoran], Yang, X.F.[Xiao-Fei], Lu, S.J.[Shi-Jian], Guan, D.[Dayan], Huang, J.X.[Jia-Xing],
FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation,
PandRS(176), 2021, pp. 237-249.
Elsevier DOI 2106
LiDAR, Point cloud, Semantic segmentation, Spherical projection, Autonomous driving, Scene understanding BibRef

Laupheimer, D.[Dominik], Haala, N.[Norbert],
Juggling with representations: On the information transfer between imagery, point clouds, and meshes for multi-modal semantics,
PandRS(176), 2021, pp. 55-68.
Elsevier DOI 2106
Multi-modality, Data fusion, 3D textured mesh, 3D point cloud, Imagery, Ground truth, Semantic segmentation BibRef

Krisanski, S.[Sean], Taskhiri, M.S.[Mohammad Sadegh], Aracil, S.G.[Susana Gonzalez], Herries, D.[David], Turner, P.[Paul],
Sensor Agnostic Semantic Segmentation of Structurally Diverse and Complex Forest Point Clouds Using Deep Learning,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Yue, Y.C.[Yu-Chun], Zhou, W.J.[Wu-Jie], Lei, J.S.[Jing-Sheng], Yu, L.[Lu],
Two-Stage Cascaded Decoder for Semantic Segmentation of RGB-D Images,
SPLetters(28), 2021, pp. 1115-1119.
IEEE DOI 2106
Semantics, Image segmentation, Feature extraction, Decoding, Sun, Training, Deep learning, RGB-d image, multilevel feature fusion BibRef

Lamas, D.[Daniel], Soilán, M.[Mario], Grandío, J.[Javier], Riveiro, B.[Belén],
Automatic Point Cloud Semantic Segmentation of Complex Railway Environments,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Liu, H.[Hao], Guo, Y.L.[Yu-Lan], Ma, Y.N.[Yan-Ni], Lei, Y.J.[Yin-Jie], Wen, G.J.[Gong-Jian],
Semantic Context Encoding for Accurate 3D Point Cloud Segmentation,
MultMed(23), 2021, pp. 2045-2055.
IEEE DOI 2107
Semantics, Image segmentation, Encoding, Convolution, semantic context BibRef

Ma, Y.N.[Yan-Ni], Guo, Y.L.[Yu-Lan], Liu, H.[Hao], Lei, Y.J.[Yin-Jie], Wen, G.J.[Gong-Jian],
Global Context Reasoning for Semantic Segmentation of 3D Point Clouds,
WACV20(2920-2929)
IEEE DOI 2006
Semantics, Cognition, Convolution, Feature extraction, Task analysis 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

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],
Learning Semantic Segmentation of Large-Scale Point Clouds With Random Sampling,
PAMI(44), No. 11, November 2022, pp. 8338-8354.
IEEE DOI 2210
BibRef
Earlier:
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds,
CVPR20(11105-11114)
IEEE DOI 2008
Semantics, Memory management, Task analysis, Sampling methods, Space exploration, Feature extraction, Large-scale point clouds, local feature aggregation. Semantics, Feature extraction, Encoding, Benchmark testing BibRef

Hu, Q.Y.[Qing-Yong], Yang, B.[Bo], Fang, G.C.[Guang-Chi], Guo, Y.L.[Yu-Lan], Leonardis, A.[Aleš], Trigoni, N.[Niki], Markham, A.[Andrew],
SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds,
ECCV22(XXVII:600-619).
Springer DOI 2211
BibRef

Rim, B.[Beanbonyka], Lee, A.[Ahyoung], Hong, M.[Min],
Semantic Segmentation of Large-Scale Outdoor Point Clouds by Encoder-Decoder Shared MLPs with Multiple Losses,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Liu, L.M.[Li-Man], Yu, J.J.[Jin-Jin], Tan, L.Y.[Long-Yu], Su, W.J.[Wan-Juan], Zhao, L.[Lin], Tao, W.B.[Wen-Bing],
Semantic Segmentation of 3D Point Cloud Based on Spatial Eight-Quadrant Kernel Convolution,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zhou, W.[Wujie], Yuan, J.Z.[Jian-Zhong], Lei, J.S.[Jing-Sheng], Luo, T.[Ting],
TSNet: Three-Stream Self-Attention Network for RGB-D Indoor Semantic Segmentation,
IEEE_Int_Sys(36), No. 4, July 2021, pp. 73-78.
IEEE DOI 2109
Semantics, Convolution, Feature extraction, Image segmentation, Streaming media, Spatial resolution, Data mining, RGB-D, indoor semantic segmentation BibRef

Zhao, Y.F.[Yi-Fan], Zhao, J.W.[Jia-Wei], Li, J.[Jia], Chen, X.W.[Xiao-Wu],
RGB-D Salient Object Detection With Ubiquitous Target Awareness,
IP(30), 2021, pp. 7717-7731.
IEEE DOI 2109
Object detection, Feature extraction, Fuses, Task analysis, Logic gates, Estimation, Image edge detection, ubiquitous target awareness BibRef

Zhou, W.J.[Wu-Jie], Liu, J.F.[Jin-Fu], Lei, J.S.[Jing-Sheng], Yu, L.[Lu], Hwang, J.N.[Jenq-Neng],
GMNet: Graded-Feature Multilabel-Learning Network for RGB-Thermal Urban Scene Semantic Segmentation,
IP(30), 2021, pp. 7790-7802.
IEEE DOI 2109
Image segmentation, Semantics, Feature extraction, Decoding, Temperature sensors, Robot sensing systems, Motion segmentation, refinement strategy BibRef

Feng, M.T.[Ming-Tao], Zhang, L.[Liang], Lin, X.F.[Xue-Fei], Gilani, S.Z.[Syed Zulqarnain], Mian, A.[Ajmal],
Point attention network for semantic segmentation of 3D point clouds,
PR(107), 2020, pp. 107446.
Elsevier DOI 2008
Semantic segmentation, 3D point cloud, Point attention network, Deep learning BibRef

Ibrahim, M.[Muhammad], Akhtar, N.[Naveed], Anwar, S.[Saeed], Mian, A.[Ajmal],
SAT3D: Slot Attention Transformer for 3D Point Cloud Semantic Segmentation,
ITS(24), No. 5, May 2023, pp. 5456-5466.
IEEE DOI 2305
Point cloud compression, Transformers, Semantic segmentation, Feature extraction, Task analysis, Computational modeling, self-driving BibRef

Ibrahim, M.[Muhammad], Akhtar, N.[Naveed], Ullah, K.[Khalil], Mian, A.[Ajmal],
Exploiting Structured CNNs for Semantic Segmentation of Unstructured Point Clouds from LiDAR Sensor,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Gu, Z.X.[Zhang-Xuan], Niu, L.[Li], Zhao, H.[Haohua], Zhang, L.Q.[Li-Qing],
Hard Pixel Mining for Depth Privileged Semantic Segmentation,
MultMed(23), 2021, pp. 3738-3751.
IEEE DOI 2110
Semantics, Image segmentation, Training, Task analysis, Fuses, Measurement uncertainty, Testing, Semantic segmentation, RGBD semantic segmentation BibRef

Du, J.[Jing], Cai, G.R.[Guo-Rong], Wang, Z.[Zongyue], Huang, S.F.[Shang-Feng], Su, J.[Jinhe], Marcato Junior, J.[José], Smit, J.[Julian], Li, J.[Jonathan],
ResDLPS-Net: Joint residual-dense optimization for large-scale point cloud semantic segmentation,
PandRS(182), 2021, pp. 37-51.
Elsevier DOI 2112
Large-scale point clouds, Semantic segmentation, Joint residual-dense optimization, Deep learning BibRef

He, Z.F.[Zi-Fen], Zhu, S.Y.[Shou-Ye], Huang, Y.[Ying], Zhang, Y.H.[Yin-Hui],
GECNN for Weakly Supervised Semantic Segmentation of 3D Point Clouds,
IEICE(E104-D), No. 12, December 2021, pp. 2237-2243.
WWW Link. 2112
BibRef

Zhao, L.C.[Li-Chen], Guo, J.Y.[Jin-Yang], Xu, D.[Dong], Sheng, L.[Lu],
Transformer3D-Det: Improving 3D Object Detection by Vote Refinement,
CirSysVideo(31), No. 12, December 2021, pp. 4735-4746.
IEEE DOI 2112
Object detection, Task analysis, Solid modeling, Proposals, Sensors, Feature extraction, Point cloud, neural network BibRef

Luo, N.[Nan], Wang, Y.F.[Yi-Feng], Gao, Y.[Yun], Tian, Y.M.[Yu-Min], Wang, Q.[Quan], Jing, C.[Chuan],
kNN-Based Feature Learning Network for Semantic Segmentation of Point Cloud Data,
PRL(152), 2021, pp. 365-371.
Elsevier DOI 2112
Semantic segmentation, Local features, Scene understanding, Point clod BibRef

Shi, W.J.[Wen-Jun], Xu, J.W.[Jing-Wei], Zhu, D.C.[Dong-Chen], Zhang, G.H.[Guang-Hui], Wang, X.S.[Xian-Shun], Li, J.[Jiamao], Zhang, X.L.[Xiao-Lin],
RGB-D Semantic Segmentation and Label-Oriented Voxelgrid Fusion for Accurate 3D Semantic Mapping,
CirSysVideo(32), No. 1, January 2022, pp. 183-197.
IEEE DOI 2201
Semantics, Streaming media, Feature extraction, Image segmentation, Labeling, discriminatory mask BibRef

Barnefske, E.[Eike], Sternberg, H.[Harald],
Evaluating the Quality of Semantic Segmented 3D Point Clouds,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Hu, Z.[Zeyu], Bai, X.Y.[Xu-Yang], Shang, J.X.[Jia-Xiang], Zhang, R.[Runze], Dong, J.Y.[Jia-Yu], Wang, X.[Xin], Sun, G.Y.[Guang-Yuan], Fu, H.B.[Hong-Bo], Tai, C.L.[Chiew-Lan],
VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation,
ICCV21(15468-15478)
IEEE DOI 2203
Geometry, Codes, Semantics, Deep architecture, Feature extraction, Scene analysis and understanding, Segmentation, Vision for robotics and autonomous vehicles BibRef

Zhai, R.M.[Ruo-Ming], Zou, J.[Jingui], He, Y.F.[Yi-Feng], Meng, L.Y.[Li-Yuan],
IAGC: Interactive Attention Graph Convolution Network for Semantic Segmentation of Point Clouds in Building Indoor Environment,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Song, H.[Hamin], Jo, K.[Kichun], Cho, J.[Jieun], Son, Y.[Youngrok], Kim, C.[Chansoo], Han, K.[Kwangjin],
A training dataset for semantic segmentation of urban point cloud map for intelligent vehicles,
PandRS(187), 2022, pp. 159-170.
Elsevier DOI 2205
Semantic global point cloud map, Training dataset, Semantic segmentation, Intelligent Vehicles, Urban environment BibRef

Decker, K.T.[Kevin T.], Borghetti, B.J.[Brett J.],
Composite Style Pixel and Point Convolution-Based Deep Fusion Neural Network Architecture for the Semantic Segmentation of Hyperspectral and Lidar Data,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Shuang, F.[Feng], Li, P.[Pei], Li, Y.[Yong], Zhang, Z.X.[Zhen-Xin], Li, X.[Xu],
MSIDA-Net: Point Cloud Semantic Segmentation via Multi-Spatial Information and Dual Adaptive Blocks,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Wang, P.[Puzuo], Yao, W.[Wei],
A new weakly supervised approach for ALS point cloud semantic segmentation,
PandRS(188), 2022, pp. 237-254.
Elsevier DOI 2205
Point cloud semantic segmentation, Weakly supervised learning, Entropy regularization, Consistency constraint, Pseudo-label BibRef

Gao, B.[Biao], Pan, Y.C.[Yan-Cheng], Li, C.K.[Cheng-Kun], Geng, S.[Sibo], Zhao, H.J.[Hui-Jing],
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey of Datasets and Methods,
ITS(23), No. 7, July 2022, pp. 6063-6081.
IEEE DOI 2207
Laser radar, Semantics, Deep learning, Task analysis, Autonomous vehicles, Statistical analysis, Data hunger, 3D LiDAR, deep learning BibRef

Tang, L.[Lulu], Chen, K.[Ke], Wu, C.Z.[Chao-Zheng], Hong, Y.[Yu], Jia, K.[Kui], Yang, Z.X.[Zhi-Xin],
Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors,
Cyber(52), No. 6, June 2022, pp. 4949-4959.
IEEE DOI 2207
Semantics, Shape, Task analysis, Encoding, Deep learning, Geometry, Geometric properties, point clouds, privileged learning, semantic analysis BibRef

Ballouch, Z.[Zouhair], Hajji, R.[Rafika], Poux, F.[Florent], Kharroubi, A.[Abderrazzaq], Billen, R.[Roland],
A Prior Level Fusion Approach for the Semantic Segmentation of 3D Point Clouds Using Deep Learning,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Tao, A.[An], Duan, Y.[Yueqi], Wei, Y.[Yi], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
SegGroup: Seg-Level Supervision for 3D Instance and Semantic Segmentation,
IP(31), 2022, pp. 4952-4965.
IEEE DOI 2208
Point cloud compression, Annotations, Semantics, Image segmentation, Training, Labeling, Point cloud segmentation, graph neural network BibRef

Song, W.[Wei], Li, D.[Dechao], Sun, S.[Su], Zhang, L.F.[Ling-Feng], Xin, Y.[Yu], Sung, Y.S.[Yun-Sick], Choi, R.[Ryong],
2D&3DHNet for 3D Object Classification in LiDAR Point Cloud,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Song, W.[Wei], Liu, Z.[Zhen], Guo, Y.[Ying], Sun, S.[Su], Zu, G.[Guidong], Li, M.[Maozhen],
DGPolarNet: Dynamic Graph Convolution Network for LiDAR Point Cloud Semantic Segmentation on Polar BEV,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Qian, Y.Q.[Ye-Qiang], Deng, L.[Liuyuan], Li, T.Y.[Tian-Yi], Wang, C.X.[Chun-Xiang], Yang, M.[Ming],
Gated-Residual Block for Semantic Segmentation Using RGB-D Data,
ITS(23), No. 8, August 2022, pp. 11836-11844.
IEEE DOI 2208
Logic gates, Semantics, Fuses, Feature extraction, Aggregates, Intelligent transportation systems, Image segmentation, gated mechanism BibRef

Zeng, Z.Y.[Zi-Yin], Xu, Y.Y.[Yong-Yang], Xie, Z.[Zhong], Wan, J.[Jie], Wu, W.C.[Wei-Chao], Dai, W.X.[Wen-Xia],
RG-GCN: A Random Graph Based on Graph Convolution Network for Point Cloud Semantic Segmentation,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Luo, Z.P.[Zhi-Peng], Zhang, X.B.[Xia-Bing], Lu, S.J.[Shi-Jian], Yi, S.[Shuai],
Domain consistency regularization for unsupervised multi-source domain adaptive classification,
PR(132), 2022, pp. 108955.
Elsevier DOI 2209
Domain adaptation, Transfer learning, Adversarial learning, Feature alignment BibRef

Xing, Y.[Yun], Guan, D.[Dayan], Huang, J.X.[Jia-Xing], Lu, S.J.[Shi-Jian],
Domain Adaptive Video Segmentation via Temporal Pseudo Supervision,
ECCV22(XXX:621-639).
Springer DOI 2211
BibRef

Guan, D.[Dayan], Huang, J.X.[Jia-Xing], Xiao, A.[Aoran], Lu, S.J.[Shi-Jian],
Domain Adaptive Video Segmentation via Temporal Consistency Regularization,
ICCV21(8033-8044)
IEEE DOI 2203
Adaptation models, Adaptive systems, Semantics, Data models, Adversarial machine learning, Task analysis, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Zhang, R.R.[Ren-Rui], Guo, Z.Y.[Zi-Yu], Zhang, W.[Wei], Li, K.C.[Kun-Chang], Miao, X.P.[Xu-Peng], Cui, B.[Bin], Qiao, Y.[Yu], Gao, P.[Peng], Li, H.S.[Hong-Sheng],
PointCLIP: Point Cloud Understanding by CLIP,
CVPR22(8542-8552)
IEEE DOI 2210
Point cloud compression, Knowledge engineering, Training, Visualization, Image recognition, Fuses, Vision+language BibRef

Luo, Z.P.[Zhi-Peng], Cai, Z.A.[Zhong-Ang], Zhou, C.Q.[Chang-Qing], Zhang, G.J.[Gong-Jie], Zhao, H.[Haiyu], Yi, S.[Shuai], Lu, S.J.[Shi-Jian], Li, H.S.[Hong-Sheng], Zhang, S.H.[Shang-Hang], Liu, Z.W.[Zi-Wei],
Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency,
ICCV21(8846-8855)
IEEE DOI 2203
Degradation, Codes, Annotations, Computer network reliability, Object detection, Transfer/Low-shot/Semi/Unsupervised Learning, Vision for robotics and autonomous vehicles BibRef

Peng, K.Y.[Kun-Yu], Fei, J.C.[Jun-Cong], Yang, K.L.[Kai-Lun], Roitberg, A.[Alina], Zhang, J.M.[Jia-Ming], Bieder, F.[Frank], Heidenreich, P.[Philipp], Stiller, C.[Christoph], Stiefelhagen, R.[Rainer],
MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding,
ITS(23), No. 9, September 2022, pp. 15824-15840.
IEEE DOI 2209
Semantics, Laser radar, Image segmentation, Point cloud compression, Feature extraction, Task analysis, intelligent vehicles BibRef

Zhao, L.[Lin], Xu, S.Y.[Si-Yuan], Liu, L.M.[Li-Man], Ming, D.[Delie], Tao, W.B.[Wen-Bing],
SVASeg: Sparse Voxel-Based Attention for 3D LiDAR Point Cloud Semantic Segmentation,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Rist, C.B.[Christoph B.], Emmerichs, D.[David], Enzweiler, M.[Markus], Gavrila, D.M.[Dariu M.],
Semantic Scene Completion Using Local Deep Implicit Functions on LiDAR Data,
PAMI(44), No. 10, October 2022, pp. 7205-7218.
IEEE DOI 2209
Semantics, Geometry, Robot sensing systems, Laser radar, Shape, Task analysis, LiDAR, semantic scene completion, deep implicit functions BibRef

Li, J.[Jie], Wang, P.[Peng], Han, K.[Kai], Liu, Y.[Yu],
Anisotropic Convolutional Neural Networks for RGB-D Based Semantic Scene Completion,
PAMI(44), No. 11, November 2022, pp. 8125-8138.
IEEE DOI 2210
Convolution, Semantics, Task analysis, Kernel, Solid modeling, Context modeling, Semantic scene completion, 3D scene understanding BibRef

Li, J.[Jie], Han, K.[Kai], Wang, P.[Peng], Liu, Y.[Yu], Yuan, X.,
Anisotropic Convolutional Networks for 3D Semantic Scene Completion,
CVPR20(3348-3356)
IEEE DOI 2008
Convolution, Semantics, Kernel, Feature extraction, Adaptation models, Context modeling BibRef

Li, J.[Jie], Liu, Y.[Yu], Gong, D.[Dong], Shi, Q.F.[Qin-Feng], Yuan, X.[Xia], Zhao, C.X.[Chun-Xia], Reid, I.D.[Ian D.],
RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion,
CVPR19(7685-7694).
IEEE DOI 2002
BibRef

Wei, J., Lin, G., Yap, K., Hung, T., Xie, L.,
Multi-Path Region Mining for Weakly Supervised 3D Semantic Segmentation on Point Clouds,
CVPR20(4383-4392)
IEEE DOI 2008
Task analysis, Semantics, Image segmentation, Machine learning, Aggregates BibRef

Fang, Z.[Zheng], Xiong, B.[Binyu], Liu, F.[Fei],
Sparse point-voxel aggregation network for efficient point cloud semantic segmentation,
IET-CV(16), No. 7, 2022, pp. 644-654.
DOI Link 2210
BibRef

Hao, F.[Fengda], Li, J.J.[Jiao-Jiao], Song, R.[Rui], Li, Y.S.[Yun-Song], Cao, K.L.[Kai-Lang],
Mixed Feature Prediction on Boundary Learning for Point Cloud Semantic Segmentation,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Guo, Y.C.[Yun-Chih], Weng, T.H.[Tzu-Hsuan], Fischer, R.[Robin], Fu, L.C.[Li-Chen],
3D semantic segmentation based on spatial-aware convolution and shape completion for augmented reality applications,
CVIU(224), 2022, pp. 103550.
Elsevier DOI 2211
Semantic segmentation, Scene understanding, Deep learning, Augmented reality, Magic leap BibRef

Su, Z.H.[Zhong-Hua], Zhou, G.Y.[Gui-Yun], Luo, F.[Fulin], Li, S.H.[Shi-Hua], Ma, K.K.[Kai-Kuang],
Semantic Segmentation of 3D Point Clouds Based on High Precision Range Search Network,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zhang, M.[Min], Kadam, P.[Pranav], Liu, S.[Shan], Kuo, C.C.J.[C.C. Jay],
GSIP: Green Semantic Segmentation of Large-Scale Indoor Point Clouds,
PRL(164), 2022, pp. 9-15.
Elsevier DOI 2212
Point cloud, Semantic segmentation, Indoor scene understanding, Green learning, unsupervised learning BibRef

Chen, M.[Mohan], Zhang, L.[Li], Feng, R.[Rui], Xue, X.Y.[Xiang-Yang], Feng, J.F.[Jian-Feng],
Rethinking Local and Global Feature Representation for Dense Prediction,
PR(135), 2023, pp. 109168.
Elsevier DOI 2212
Dense prediction, Vision transformer, Semantic segmentation, Depth estimation, Object detection BibRef

Vierhub-Lorenz, V.[Valentin], Kellner, M.[Maximilian], Zipfel, O.[Oliver], Reiterer, A.[Alexander],
A Study on the Effect of Multispectral LiDAR Data on Automated Semantic Segmentation of 3D-Point Clouds,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Chen, J.Z.[Jia-Zhou], Zhan, Y.F.[Yang-Fan], Xu, Y.H.[Yang-Hui], Pan, X.[Xiang],
FAFNet: Fully aligned fusion network for RGBD semantic segmentation based on hierarchical semantic flows,
IET-IPR(17), No. 1, 2023, pp. 32-41.
DOI Link 2301
BibRef

Yang, E.[Enquan], Zhou, W.[Wujie], Qian, X.H.[Xiong-Hong], Yu, L.[Lu],
MGCNet: Multilevel Gated Collaborative Network for RGB-D Semantic Segmentation of Indoor Scene,
SPLetters(29), 2022, pp. 2567-2571.
IEEE DOI 2301
Feature extraction, Convolution, Data mining, Logic gates, Decoding, Kernel, Semantic segmentation, RGB-D semantic segmentation, serial-parallel alternation strategy BibRef

Li, X.Y.[Xing-Ye], Zhang, L.[Ling], Zhu, Z.G.[Zhi-Gang],
SnapshotNet: Self-supervised feature learning for point cloud data segmentation using minimal labeled data,
CVIU(216), 2022, pp. 103339.
Elsevier DOI 2202
Self-supervision, Point cloud, Semantic segmentation BibRef

Wang, F.[Fei], Zhuang, Y.[Yan], Zhang, H.[Hong], Gu, H.[Hong],
Real-Time 3-D Semantic Scene Parsing With LiDAR Sensors,
Cyber(52), No. 3, March 2022, pp. 1351-1363.
IEEE DOI 2203
Convolution, Semantics, Real-time systems, Laser radar, Tensile stress, Task analysis, 3-D convolutional neural network, sparse (ST) BibRef

Wang, P.[Puzuo], Yao, W.[Wei], Shao, J.[Jie],
One Class One Click: Quasi scene-level weakly supervised point cloud semantic segmentation with active learning,
PandRS(204), 2023, pp. 89-104.
Elsevier DOI 2310
Point cloud, Semantic segmentation, Weakly supervised learning, Active learning BibRef

Yuan, Z.M.[Zhi-Min], Wen, C.L.[Cheng-Lu], Cheng, M.[Ming], Su, Y.F.[Yan-Fei], Liu, W.Q.[Wei-Quan], Yu, S.S.[Shang-Shu], Wang, C.[Cheng],
Category-Level Adversaries for Outdoor LiDAR Point Clouds Cross-Domain Semantic Segmentation,
ITS(24), No. 2, February 2023, pp. 1982-1993.
IEEE DOI 2302
Point cloud compression, Feature extraction, Task analysis, Laser radar, Training, Semantics, Unsupervised domain adaptation, semantic segmentation BibRef

Kouhi, R.M.[Reza Mahmoudi], Daniel, S.[Sylvie], Gigučre, P.[Philippe],
Data Preparation Impact on Semantic Segmentation of 3D Mobile LiDAR Point Clouds Using Deep Neural Networks,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Yin, X.Q.[Xiao-Qing], Li, X.[Xu], Ni, P.Z.[Pei-Zhou], Xu, Q.M.[Qi-Min], Kong, D.[Dong],
A Novel Real-Time Edge-Guided LiDAR Semantic Segmentation Network for Unstructured Environments,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Zhao, L.[Lin], Tao, W.B.[Wen-Bing],
JSNet++: Dynamic Filters and Pointwise Correlation for 3D Point Cloud Instance and Semantic Segmentation,
CirSysVideo(33), No. 4, April 2023, pp. 1854-1867.
IEEE DOI 2304
Point cloud compression, Semantics, Correlation, Task analysis, Memory management, pointwise correlation BibRef

Shao, H.H.[Hui-Hui], Bai, J.[Jing], Wu, R.[Rusong], Jiang, J.Z.[Jin-Zhe], Liang, H.B.[Hong-Bo],
FGPNet: A weakly supervised fine-grained 3D point clouds classification network,
PR(139), 2023, pp. 109509.
Elsevier DOI 2304
BibRef
And: Corrigendum: PR(151), 2024, pp. 110379.
Elsevier DOI 2404
3D point clouds, Fine-grained classification, Context-aware feature extraction, SimAM-Capsule aggregation, Spatial relationships BibRef

Grilli, E.[Eleonora], Daniele, A.[Alessandro], Bassier, M.[Maarten], Remondino, F.[Fabio], Serafini, L.[Luciano],
Knowledge Enhanced Neural Networks for Point Cloud Semantic Segmentation,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

He, S.T.[Shu-Ting], Jiang, X.D.[Xu-Dong], Jiang, W.[Wei], Ding, H.H.[Heng-Hui],
Prototype Adaption and Projection for Few- and Zero-Shot 3D Point Cloud Semantic Segmentation,
IP(32), 2023, pp. 3199-3211.
IEEE DOI 2306
Prototypes, Point cloud compression, Semantics, Feature extraction, Semantic segmentation, Task analysis, self-reconstruction BibRef

Cheng, H.X.[Hui-Xian], Han, X.F.[Xian-Feng], Xiao, G.Q.[Guo-Qiang],
TransRVNet: LiDAR Semantic Segmentation With Transformer,
ITS(24), No. 6, June 2023, pp. 5895-5907.
IEEE DOI 2306
Transformers, Point cloud compression, Laser radar, Semantic segmentation, Semantics, Convolutional neural networks, autonomous driving BibRef

Rong, M.Q.[Meng-Qi], Cui, H.[Hainan], Shen, S.H.[Shu-Han],
Efficient 3D Scene Semantic Segmentation via Active Learning on Rendered 2D Images,
IP(32), 2023, pp. 3521-3535.
IEEE DOI 2307
Solid modeling, Semantic segmentation, Semantics, Rendering (computer graphics), Point cloud compression, rendered multi-view images BibRef

Pan, Y.C.[Yan-Cheng], Xie, F.[Fan], Zhao, H.J.[Hui-Jing],
Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Data,
ITS(24), No. 7, July 2023, pp. 6955-6970.
IEEE DOI 2307
Data models, Solid modeling, Semantic segmentation, Laser radar, Predictive models, Task analysis, 3D LiDAR, semantic segmentation, class imbalance BibRef

Hoyer, L.[Lukas], Dai, D.X.[Deng-Xin], Wang, Q.[Qin], Chen, Y.H.[Yu-Hua], Van Gool, L.J.[Luc J.],
Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation,
IJCV(131), No. 8, August 2023, pp. 2070-2096.
Springer DOI 2307
BibRef

Hoyer, L.[Lukas], Dai, D.X.[Deng-Xin], Chen, Y.H.[Yu-Hua], Köring, A.[Adrian], Saha, S.[Suman], Van Gool, L.J.[Luc J.],
Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation,
CVPR21(11125-11135)
IEEE DOI 2111
Geometry, Training, Image segmentation, Annotations, Semantics, Estimation, Training data BibRef

Gong, R.[Rui], Wang, Q.[Qin], Danelljan, M.[Martin], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Continuous Pseudo-Label Rectified Domain Adaptive Semantic Segmentation with Implicit Neural Representations,
CVPR23(7225-7235)
IEEE DOI 2309
BibRef

Wang, Q.[Qin], Dai, D.X.[Deng-Xin], Hoyer, L.[Lukas], Van Gool, L.J.[Luc J.], Fink, O.[Olga],
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation,
ICCV21(8495-8505)
IEEE DOI 2203
Bridges, Visualization, Correlation, Navigation, Semantics, Estimation, Transfer/Low-shot/Semi/Unsupervised Learning, Vision for robotics and autonomous vehicles BibRef

Humblot-Renaux, G.[Galadrielle], Jensen, S.B.[Simon Buus], Mřgelmose, A.[Andreas],
From CAD Models to Soft Point Cloud Labels: An Automatic Annotation Pipeline for Cheaply Supervised 3D Semantic Segmentation,
RS(15), No. 14, 2023, pp. 3578.
DOI Link 2307
BibRef

Yin, F.[Fukun], Huang, Z.L.[Zi-Long], Chen, T.[Tao], Luo, G.Z.[Guo-Zhong], Yu, G.[Gang], Fu, B.[Bin],
DCNet: Large-Scale Point Cloud Semantic Segmentation With Discriminative and Efficient Feature Aggregation,
CirSysVideo(33), No. 8, August 2023, pp. 4083-4095.
IEEE DOI 2308
Point cloud compression, Semantics, Semantic segmentation, Decoding, Aggregates, Feature extraction, Semantic segmentation, attention BibRef

Peters, T.[Torben], Brenner, C.[Claus], Schindler, K.[Konrad],
Semantic segmentation of mobile mapping point clouds via multi-view label transfer,
PandRS(202), 2023, pp. 30-39.
Elsevier DOI 2308
Semantic segmentation, 3D point clouds, Multi-view, Convolutional neural network (CNN), Label transfer BibRef

Zhou, W.[Wujie], Yang, E.[Enquan], Lei, J.S.[Jing-Sheng], Wan, J.[Jian], Yu, L.[Lu],
PGDENet: Progressive Guided Fusion and Depth Enhancement Network for RGB-D Indoor Scene Parsing,
MultMed(25), 2023, pp. 3483-3494.
IEEE DOI 2309
BibRef

Chopin, J.[Jeremy], Fasquel, J.B.[Jean-Baptiste], Mouchčre, H.[Harold], Dahyot, R.[Rozenn], Bloch, I.[Isabelle],
Model-based inexact graph matching on top of DNNs for semantic scene understanding,
CVIU(235), 2023, pp. 103744.
Elsevier DOI 2310
Graph matching, Deep learning, Image segmentation, Volume segmentation, Quadratic assignment problem BibRef

Chang, M.J.[Ming-Jen], Cheng, C.J.[Chih-Jen], Hsiao, C.C.[Ching-Chun], Li, Y.H.[Yung-Hui], Huang, C.C.[Ching-Chun],
SVDnet: Singular Value Control and Distance Alignment Network for 3D Object Detection,
ITS(24), No. 9, September 2023, pp. 9281-9295.
IEEE DOI 2310
BibRef

Ru, Q.J.[Qing-Jun], Chen, G.Z.[Guang-Zhu], Zuo, T.[Tingyu], Liao, X.J.[Xiao-Juan],
Cross-Modal Transformer for RGB-D semantic segmentation of production workshop objects,
PR(144), 2023, pp. 109862.
Elsevier DOI 2310
Cross-Modal, Production workshop object, RGB-D, Semantic segmentation, Transformer BibRef

Weng, T.[Tingyu], Xiao, J.[Jun], Yan, F.L.[Fei-Long], Jiang, H.Y.[Hai-Yong],
Context-Aware 3D Point Cloud Semantic Segmentation With Plane Guidance,
MultMed(25), 2023, pp. 6653-6664.
IEEE DOI Code:
WWW Link. 2311
BibRef

Ji, H.[Hao], Yang, S.[Sansheng], Jiang, Z.P.[Zhi-Peng], Zhang, J.J.[Jian-Jun], Guo, S.[Shuhao], Li, G.[Gaorui], Zhong, S.[Saishang], Liu, Z.[Zheng], Xie, Z.[Zhong],
BEMF-Net: Semantic Segmentation of Large-Scale Point Clouds via Bilateral Neighbor Enhancement and Multi-Scale Fusion,
RS(15), No. 22, 2023, pp. 5342.
DOI Link 2311
BibRef

Zhang, R.X.[Rui-Xiang], Chen, S.Y.[Si-Yang], Wang, X.Y.[Xu-Ying], Zhang, Y.S.[Yun-Sheng],
IPCONV: Convolution with Multiple Different Kernels for Point Cloud Semantic Segmentation,
RS(15), No. 21, 2023, pp. 5136.
DOI Link 2311
BibRef

Zhou, W.[Wujie], Yue, Y.C.[Yu-Chun], Fang, M.[Meixin], Mao, S.S.[Shan-Shan], Yang, R.W.[Rong-Wang], Yu, L.[Lu],
AMCFNet: Asymmetric multiscale and crossmodal fusion network for RGB-D semantic segmentation in indoor service robots,
JVCIR(97), 2023, pp. 103951.
Elsevier DOI 2312
Multiscale feature, Crossmodal fusion, Differential feature integration, RGB-D information, Semantic segmentation BibRef

Shi, H.Y.[Han-Yu], Li, R.[Ruibo], Liu, F.[Fayao], Lin, G.S.[Guo-Sheng],
Temporal Feature Matching and Propagation for Semantic Segmentation on 3D Point Cloud Sequences,
CirSysVideo(33), No. 12, December 2023, pp. 7491-7502.
IEEE DOI 2312
BibRef

Rong, M.Q.[Meng-Qi], Shen, S.H.[Shu-Han],
3D Semantic Segmentation of Aerial Photogrammetry Models Based on Orthographic Projection,
CirSysVideo(33), No. 12, December 2023, pp. 7425-7437.
IEEE DOI 2312
BibRef

Wu, H.[Hua], Huang, Z.[Zhe], Zheng, W.[Wanhao], Bai, X.J.[Xiao-Jing], Sun, L.[Li], Pu, M.Y.[Meng-Yang],
SSGAM-Net: A Hybrid Semi-Supervised and Supervised Network for Robust Semantic Segmentation Based on Drone LiDAR Data,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Wang, T.[Tichao], Hao, F.[Fusheng], Cui, G.S.[Guo-Sheng], Wu, F.[Fuxiang], Yang, M.J.[Meng-Jie], Zhang, Q.[Qieshi], Cheng, J.[Jun],
Two-stage feature distribution rectification for few-shot point cloud semantic segmentation,
PRL(177), 2024, pp. 142-149.
Elsevier DOI 2401
Few-shot learning, Point cloud semantic segmentation, Feature distribution rectification BibRef

Ballouch, Z.[Zouhair], Hajji, R.[Rafika], Kharroubi, A.[Abderrazzaq], Poux, F.[Florent], Billen, R.[Roland],
Investigating Prior-Level Fusion Approaches for Enriched Semantic Segmentation of Urban LiDAR Point Clouds,
RS(16), No. 2, 2024, pp. 329.
DOI Link 2402
BibRef

Zhang, Y.S.[Yun-Sheng], Yao, J.G.[Jian-Guo], Zhang, R.X.[Rui-Xiang], Wang, X.Y.[Xu-Ying], Chen, S.Y.[Si-Yang], Fu, H.[Han],
HAVANA: Hard Negative Sample-Aware Self-Supervised Contrastive Learning for Airborne Laser Scanning Point Cloud Semantic Segmentation,
RS(16), No. 3, 2024, pp. 485.
DOI Link 2402
BibRef

Zhao, L.[Lin], Zhou, H.[Hui], Zhu, X.G.[Xin-Ge], Song, X.[Xiao], Li, H.S.[Hong-Sheng], Tao, W.B.[Wen-Bing],
LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation,
MultMed(26), 2024, pp. 1158-1168.
IEEE DOI 2402
Laser radar, Cameras, Point cloud compression, Semantics, Semantic segmentation, Synchronization, LiDAR and Camera, weak spatiotemporal synchronization BibRef

Niu, Y.C.[Ying-Chun], Yin, J.Q.[Jian-Qin],
Weakly supervised point cloud semantic segmentation with the fusion of heterogeneous network features,
IVC(142), 2024, pp. 104916.
Elsevier DOI 2402
Weakly supervised, Point cloud, Artifical intelligence, 3D computer vision BibRef

Ni, P.Z.[Pei-Zhou], Li, X.[Xu], Xu, W.[Wang], Zhou, X.J.[Xiao-Jing], Jiang, T.[Tao], Hu, W.M.[Wei-Ming],
Robust 3D Semantic Segmentation Method Based on Multi-Modal Collaborative Learning,
RS(16), No. 3, 2024, pp. 453.
DOI Link 2402
BibRef

Yang, J.[Jun], Bai, L.Z.[Li-Zhi], Sun, Y.R.[Yao-Ru], Tian, C.Q.[Chun-Qi], Mao, M.[Maoyu], Wang, G.R.[Guo-Run],
Pixel Difference Convolutional Network for RGB-D Semantic Segmentation,
CirSysVideo(34), No. 3, March 2024, pp. 1481-1492.
IEEE DOI 2403
Convolution, Semantic segmentation, Semantics, Feature extraction, Convolutional neural networks, Kernel, Semantic segmentation, cascade large kernel BibRef

Han, J.W.[Jia-Wei], Liu, K.Q.[Kai-Qi], Li, W.[Wei], Chen, G.Z.[Guang-Zhi], Wang, W.G.[Wen-Guang], Zhang, F.[Feng],
A Large-Scale Network Construction and Lightweighting Method for Point Cloud Semantic Segmentation,
IP(33), 2024, pp. 2004-2017.
IEEE DOI 2403
Point cloud compression, Semantic segmentation, Task analysis, Knowledge engineering, Transformers, Image coding, information combination BibRef

Zheng, X.Y.[Xiao-Yun], Liao, L.W.[Li-Wei], Jiao, J.B.[Jian-Bo], Gao, F.[Feng], Wang, R.G.[Rong-Gang],
Surface-SOS: Self-Supervised Object Segmentation via Neural Surface Representation,
IP(33), 2024, pp. 2018-2031.
IEEE DOI Code:
WWW Link. 2403
Image segmentation, Videos, Object segmentation, Motion segmentation, Geometry, Training, multi-view object segmentation BibRef

Sun, T.F.[Tian-Fang], Zhang, Z.Z.[Zhi-Zhong], Tan, X.[Xin], Qu, Y.Y.[Yan-Yun], Xie, Y.[Yuan],
Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning,
IP(33), 2024, pp. 1838-1852.
IEEE DOI 2403
Point cloud compression, Labeling, Laser radar, Annotations, Training, Semantic segmentation, point cloud semantic segmentation BibRef

Zhang, Y.C.[Ya-Chao], Qu, Y.Y.[Yan-Yun], Xie, Y.[Yuan], Li, Z.H.[Zong-Hao], Zheng, S.S.[Shan-Shan], Li, C.H.[Cui-Hua],
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation,
ICCV21(15500-15508)
IEEE DOI 2203
Point cloud compression, Correlation, Network topology, Annotations, Semantics, Supervised learning, Vision for robotics and autonomous vehicles BibRef

Li, M.T.[Meng-Tian], Xie, Y.[Yuan], Shen, Y.H.[Yun-Hang], Ke, B.[Bo], Qiao, R.Z.[Rui-Zhi], Ren, B.[Bo], Lin, S.H.[Shao-Hui], Ma, L.Z.[Li-Zhuang],
HybridCR: Weakly-Supervised 3D Point Cloud Semantic Segmentation via Hybrid Contrastive Regularization,
CVPR22(14910-14919)
IEEE DOI 2210
Point cloud compression, Training, Costs, Shape, Computational modeling, Computer vision for social good, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

Li, D.Q.[Ding-Quan], Ma, K.[Kede], Wang, J.[Jing], Li, G.[Ge],
Hierarchical Prior-Based Super Resolution for Point Cloud Geometry Compression,
IP(33), 2024, pp. 1965-1976.
IEEE DOI Code:
WWW Link. 2403
Point cloud compression, Geometry, Superresolution, Image coding, Image reconstruction, coarse-to-fine super resolution BibRef

Shu, Z.Y.[Zhen-Yu], Wu, T.[Teng], Shen, J.J.[Jia-Jun], Xin, S.Q.[Shi-Qing], Liu, L.G.[Li-Gang],
Semi-Supervised 3D Shape Segmentation via Self Refining,
IP(33), 2024, pp. 2044-2057.
IEEE DOI 2403
Shape, Training, Task analysis, Labeling, Faces, Vectors, 3D shape segmentation, semi-supervised, deep neural network BibRef

Liang, Y.C.[You-Cheng], Lu, J.[Jian], Chen, X.G.[Xiao-Gai], Zhang, K.B.[Kai-Bing],
High-Performance Feature Extraction Network for Point Cloud Semantic Segmentation,
SPLetters(31), 2024, pp. 904-908.
IEEE DOI 2404
Feature extraction, Point cloud compression, Transformers, Vectors, Data mining, Convolution, Surface treatment, 3D point cloud, geometric surface BibRef

Wang, J.Y.[Jing-Yi], Liu, Y.[Yu], Tan, H.L.[Han-Lin], Zhang, M.J.[Mao-Jun],
A survey on weakly supervised 3D point cloud semantic segmentation,
IET-CV(18), No. 3, 2024, pp. 329-342.
DOI Link 2404
learning (artificial intelligence), unsupervised learning BibRef

Wang, J.Y.[Jing-Yi], He, J.Y.[Jing-Yang], Liu, Y.[Yu], Chen, C.[Chen], Zhang, M.J.[Mao-Jun], Tan, H.L.[Han-Lin],
Multi-Scale Classification and Contrastive Regularization: Weakly Supervised Large-Scale 3D Point Cloud Semantic Segmentation,
RS(16), No. 17, 2024, pp. 3319.
DOI Link 2409
BibRef

Wen, J.J.[Jun-Jie], Ma, J.[Jie], Zhao, Y.[Yuehua], Nie, T.[Tong], Sun, M.X.[Meng-Xuan], Fan, Z.M.[Zi-Ming],
Point cloud semantic segmentation based on local feature fusion and multilayer attention network,
IET-CV(18), No. 3, 2024, pp. 381-392.
DOI Link 2404
image segmentation, pattern recognition BibRef

Chen, R.X.[Rui-Xing], Wu, J.[Jun], Luo, Y.[Ying], Xu, G.[Gang],
PointMM: Point Cloud Semantic Segmentation CNN under Multi-Spatial Feature Encoding and Multi-Head Attention Pooling,
RS(16), No. 7, 2024, pp. 1246.
DOI Link 2404
BibRef

Massa, K.J.L.[Kelian J.L.], Grobler, H.[Hans],
Adapting projection-based LiDAR semantic segmentation to natural domains,
JVCIR(100), 2024, pp. 104111.
Elsevier DOI 2405
Semantic analysis, Semantic segmentation, LiDAR, Natural data, Projection, Fusion BibRef

Yazici, Z.A.[Ziya Ata], Öksüz, I.[Ilkay], Ekenel, H.K.[Hazim Kemal],
GLIMS: Attention-guided lightweight multi-scale hybrid network for volumetric semantic segmentation,
IVC(146), 2024, pp. 105055.
Elsevier DOI Code:
WWW Link. 2405
Medical image segmentation, Convolutional neural network, Vision transformer, Multi-scale features, Attention-guidance BibRef

Yuan, T.B.[Tie-Biao], Yu, Y.Y.[Yang-Yang], Wang, X.L.[Xiao-Long],
Semantic segmentation of large-scale point clouds by integrating attention mechanisms and transformer models,
IVC(146), 2024, pp. 105019.
Elsevier DOI 2405
Point cloud semantic segmentation, Large-scale point cloud, Transformer, Slot attention, Loss function BibRef

Zhang, J.J.[Jian-Jun], Jiang, Z.P.[Zhi-Peng], Qiu, Q.J.[Qin-Jun], Liu, Z.[Zheng],
TCFAP-Net: Transformer-based Cross-feature Fusion and Adaptive Perception Network for large-scale point cloud semantic segmentation,
PR(154), 2024, pp. 110630.
Elsevier DOI Code:
WWW Link. 2406
Transformer, Attention, Semantic segmentation, Point cloud scenarios BibRef

Yan, X.[Xu], Zheng, C.D.[Chao-Da], Xue, Y.[Ying], Li, Z.[Zhen], Cui, S.G.[Shu-Guang], Dai, D.X.[Deng-Xin],
Benchmarking the Robustness of LiDAR Semantic Segmentation Models,
IJCV(132), No. 7, July 2024, pp. Pages2674-2697.
Springer DOI 2406
BibRef

Zhou, X.W.[Xiao-Wei], Guo, H.Y.[Hao-Yu], Peng, S.[Sida], Xiao, Y.X.[Yu-Xi], Lin, H.T.[Hao-Tong], Wang, Q.Q.[Qian-Qian], Zhang, G.F.[Guo-Feng], Bao, H.J.[Hu-Jun],
Neural 3D Scene Reconstruction With Indoor Planar Priors,
PAMI(46), No. 9, September 2024, pp. 6355-6366.
IEEE DOI 2408
Image reconstruction, Semantics, Geometry, Semantic segmentation, Rendering (computer graphics), Optimization, 3D reconstruction, the Atlanta-world assumption BibRef

Mu, T.J.[Tai-Jiang], Shen, M.Y.[Ming-Yuan], Lai, Y.K.[Yu-Kun], Hu, S.M.[Shi-Min],
Learning Virtual View Selection for 3D Scene Semantic Segmentation,
IP(33), 2024, pp. 4159-4172.
IEEE DOI Code:
WWW Link. 2408
BibRef

Liu, Y.C.[Yong-Chang], Liu, Y.W.[Ya-Wen], Duan, Y.S.[Yan-Song],
MVG-Net: LiDAR Point Cloud Semantic Segmentation Network Integrating Multi-View Images,
RS(16), No. 15, 2024, pp. 2821.
DOI Link 2408
BibRef

Khan, M.Q., Shahzad, M., Khan, S.A., Fraz, M.M., Zhu, X.X.,
Beyond local patches: Preserving global-local interactions by enhancing self-attention via 3D point cloud tokenization,
PR(155), 2024, pp. 110712.
Elsevier DOI 2408
3D point cloud, Transformer, Self-attention, Segmentation, Classification BibRef

Li, M.T.[Meng-Tian], Lin, S.H.[Shao-Hui], Wang, Z.H.[Zi-Han], Shen, Y.H.[Yun-Hang], Zhang, B.C.[Bao-Chang], Ma, L.Z.[Li-Zhuang],
Class-Imbalanced Semi-Supervised Learning for Large-Scale Point Cloud Semantic Segmentation via Decoupling Optimization,
PR(156), 2024, pp. 110701.
Elsevier DOI 2408
3D point cloud, Class-imbalanced learning, Semi-supervised learning, Semantic segmentation BibRef

Du, A.[Anan], Zhou, T.F.[Tian-Fei], Pang, S.[Shuchao], Wu, Q.[Qiang], Zhang, J.[Jian],
PCL: Point Contrast and Labeling for Weakly Supervised Point Cloud Semantic Segmentation,
MultMed(26), 2024, pp. 8902-8914.
IEEE DOI 2408
Point cloud compression, Semantic segmentation, Task analysis, Self-supervised learning, Convolution, Training, Point cloud, contrastive learning BibRef

Zhou, C.[Ce], Shu, Z.[Zhaokun], Shi, L.[Li], Ling, Q.[Qiang],
Semantic segmentation for large-scale point clouds based on hybrid attention and dynamic fusion,
PR(156), 2024, pp. 110798.
Elsevier DOI 2408
Hybrid attention, Dynamic fusion, Point cloud, Semantic segmentation BibRef

Xuan, W.H.[Wei-Hao], Qi, H.[Heli], Xiao, A.[Aoran],
TSG-Seg: Temporal-selective guidance for semi-supervised semantic segmentation of 3D LiDAR point clouds,
PandRS(216), 2024, pp. 217-228.
Elsevier DOI Code:
WWW Link. 2408
3D point cloud, LiDAR, Semantic segmentation, Semi-supervised learning, Spatio-temporal learning, Autonomous driving BibRef

Cheng, T.H.[Tian-Heng], Jiang, H.[Haoyi], Chen, S.[Shaoyu], Liao, B.[Bencheng], Zhang, Q.[Qian], Liu, W.Y.[Wen-Yu], Wang, X.G.[Xing-Gang],
Learning accurate monocular 3D voxel representation via bilateral voxel transformer,
IVC(150), 2024, pp. 105237.
Elsevier DOI 2409
3D semantic scene completion, Occupancy networks, Scene understanding, Voxel transformers, Autonomous driving BibRef

Liang, Z.X.[Zhuan-Xin], Lai, X.D.[Xu-Dong],
Multilevel Geometric Feature Embedding in Transformer Network for ALS Point Cloud Semantic Segmentation,
RS(16), No. 18, 2024, pp. 3386.
DOI Link 2410
BibRef

Koszyk, J.[Joanna], Jasinska, A.[Aleksandra], Pargiela, K.[Karolina], Malczewska, A.[Anna], Grzelka, K.[Kornelia], Bieda, A.[Agnieszka], Ambrozinski, L.[Lukasz],
Semantic Segmentation-Driven Integration of Point Clouds from Mobile Scanning Platforms in Urban Environments,
RS(16), No. 18, 2024, pp. 3434.
DOI Link 2410
BibRef

Jiang, Z.F.[Ze-Feng], Yao, B.C.[Bao-Chen], Song, K.K.[Kang-Kang], Qiu, X.J.[Xiao-Jie], Peng, C.B.[Cheng-Bin],
Point Cloud Semantic Segmentation by Adaptively Fusing Information With Varying Distances,
SPLetters(31), 2024, pp. 2565-2569.
IEEE DOI 2410
Point cloud compression, Feature extraction, Semantic segmentation, Vectors, Accuracy, Training, Optimization, varing distance BibRef

Mei, J.B.[Jian-Biao], Yang, Y.[Yu], Wang, M.M.[Meng-Meng], Zhu, J.Y.[Jun-Yu], Ra, J.W.[Jong-Won], Ma, Y.[Yukai], Li, L.J.[Lai-Jian], Liu, Y.[Yong],
Camera-Based 3D Semantic Scene Completion With Sparse Guidance Network,
IP(33), 2024, pp. 5468-5481.
IEEE DOI Code:
WWW Link. 2410
Semantics, Geometry, Feature extraction, Solid modeling, Proposals, Cameras, Convergence, Autonomous vehicles, Visualization, voxel aggregation BibRef

Tan, M.K.[Ming-Kui], Zhuang, Z.W.[Zhuang-Wei], Chen, S.[Sitao], Li, R.[Rong], Jia, K.[Kui], Wang, Q.C.[Qi-Cheng], Li, Y.Q.[Yuan-Qing],
EPMF: Efficient Perception-Aware Multi-Sensor Fusion for 3D Semantic Segmentation,
PAMI(46), No. 12, December 2024, pp. 8258-8273.
IEEE DOI 2411
BibRef
Earlier: A2, A4, A5, A6, A7, A1, Only:
Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation,
ICCV21(16260-16270)
IEEE DOI 2203
Point cloud compression, Laser radar, Cameras, Semantic segmentation, Feature extraction, Sensors, scene understanding. Fuses, Semantics, Collaboration, Benchmark testing, Vision for robotics and autonomous vehicles BibRef

Xiang, P.C.[Peng-Cheng], Yao, B.C.[Bao-Chen], Jiang, Z.F.[Ze-Feng], Peng, C.B.[Cheng-Bin],
Self-Enhanced Feature Fusion for RGB-D Semantic Segmentation,
SPLetters(31), 2024, pp. 3015-3019.
IEEE DOI 2411
Semantics, Feature extraction, Image edge detection, Semantic segmentation, Training, Decoding, Convolution, Fuses, normalizing flow BibRef

Sun, T.F.[Tian-Fang], Zhang, Z.Z.[Zhi-Zhong], Tan, X.[Xin], Peng, Y.[Yong], Qu, Y.[Yanyun], Xie, Y.[Yuan],
Uni-to-Multi Modal Knowledge Distillation for Bidirectional LiDAR-Camera Semantic Segmentation,
PAMI(46), No. 12, December 2024, pp. 11059-11072.
IEEE DOI 2411
Laser radar, Point cloud compression, Cameras, Robustness, Semantics, Data augmentation, 3D semantic segmentation, cross-modal knowledge distillation BibRef

Lin, F.F.[Fang-Fang], Lin, T.L.[Tian-Liang], Yao, Y.[Yu], Ren, H.L.[Hao-Ling], Wu, J.D.[Jiang-Dong], Cai, Q.P.[Qi-Peng],
VPA-Net: A visual perception assistance network for 3d lidar semantic segmentation,
PR(158), 2025, pp. 111014.
Elsevier DOI 2411
Multi-sensor fusion, Semantic segmentation, 3D point cloud, Autonomous driving, Intelligent perception, Dataset BibRef

Wu, J.W.[Jun-Wei], Sun, M.J.[Ming-Jie], Xu, H.T.[Hao-Tian], Jiang, C.[Chenru], Ma, W.[Wuwei], Zhang, Q.[Quan],
Class Agnostic and Specific Consistency Learning for Weakly-Supervised Point Cloud Semantic Segmentation,
PR(158), 2025, pp. 111067.
Elsevier DOI Code:
WWW Link. 2411
3d point cloud, Weakly-supervised learning, Consistency learning BibRef


Xu, J.H.[Jia-Hua], Zuo, S.[Si], Wei, C.F.[Chen-Feng], Zhou, W.[Wei],
LiSD: An Efficient Multi-Task Learning Framework for Lidar Segmentation and Detection,
ICIP24(3341-3347)
IEEE DOI 2411
Laser radar, Semantic segmentation, Collaboration, Object detection, Performance gain, Multitasking BibRef

Montalvo, J.[Javier], Carballeira, P.[Pablo], García-Martín, Á.[Álvaro],
Synthmanticlidar: A Synthetic Dataset for Semantic Segmentation On Lidar Imaging,
ICIP24(137-143)
IEEE DOI Code:
WWW Link. 2411
Training, Laser radar, Semantic segmentation, Transfer learning, Imaging, Labeling, Task analysis, Dataset, LiDAR Segmentation, Simulator BibRef

Royen, R.[Remco], Pataridis, K.[Kostas], van der Tempel, W.[Ward], Munteanu, A.[Adrian],
RESSCAL3D++: Joint Acquisition and Semantic Segmentation of 3D Point Clouds,
ICIP24(3547-3553)
IEEE DOI Code:
WWW Link. 2411
Point cloud compression, Image resolution, Semantic segmentation, Scalability, Semantics, Data acquisition, Point clouds, dataset BibRef

Wu, X.P.[Xiao-Pei], Hou, Y.N.[Yue-Nan], Huang, X.S.[Xiao-Shui], Lin, B.B.[Bin-Bin], He, T.[Tong], Zhu, X.G.[Xin-Ge], Ma, Y.X.[Yue-Xin], Wu, B.[Boxi], Liu, H.F.[Hai-Feng], Cai, D.[Deng], Ouyang, W.L.[Wan-Li],
TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentation,
CVPR24(15311-15320)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Training, Laser radar, Tracking, Semantic segmentation, Semantics, Switches, Multi-Modal BibRef

Chen, H.M.[Hao-Ming], Zhang, Z.Z.[Zhi-Zhong], Qu, Y.[Yanyun], Zhang, R.X.[Rui-Xin], Tan, X.[Xin], Xie, Y.[Yuan],
Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception,
CVPR24(19925-19935)
IEEE DOI Code:
WWW Link. 2410
Representation learning, Heart, Solid modeling, Semantic segmentation, Semantics, Buildings BibRef

Wu, X.Y.[Xiao-Yang], Tian, Z.[Zhuotao], Wen, X.[Xin], Peng, B.[Bohao], Liu, X.H.[Xi-Hui], Yu, K.C.[Kai-Cheng], Zhao, H.S.[Heng-Shuang],
Towards Large-Scale 3D Representation Learning with Multi-Dataset Point Prompt Training,
CVPR24(19551-19562)
IEEE DOI 2410
Training, Representation learning, Deep learning, Point cloud compression, Solid modeling, Soft sensors, 3D Semantic Segmentation BibRef

Peng, B.[Bohao], Wu, X.Y.[Xiao-Yang], Jiang, L.[Li], Chen, Y.[Yukang], Zhao, H.S.[Heng-Shuang], Tian, Z.[Zhuotao], Jia, J.Y.[Jia-Ya],
OA-CNNs: Omni-Adaptive Sparse CNNs for 3D Semantic Segmentation,
CVPR24(21305-21315)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Solid modeling, Costs, Convolution, Semantic segmentation, Heuristic algorithms, 3D semantic segmentation BibRef

Liu, Y.Q.[You-Quan], Kong, L.D.[Ling-Dong], Wu, X.Y.[Xiao-Yang], Chen, R.[Runnan], Li, X.[Xin], Pan, L.[Liang], Liu, Z.W.[Zi-Wei], Ma, Y.X.[Yue-Xin],
Multi-Space Alignments Towards Universal LiDAR Segmentation,
CVPR24(14648-14661)
IEEE DOI 2410
Training, Laser radar, Diversity reception, Propulsion, Robustness, LiDAR Segmentation, Autonomous Driving, Multi-Dataset Training, 3D Semantic Segmentation BibRef

Li, S.[Shiyao], Yang, W.M.[Wen-Ming], Liao, Q.M.[Qing-Min],
PMAFusion: Projection-Based Multi-Modal Alignment for 3D Semantic Occupancy Prediction,
LargeVM24(3627-3634)
IEEE DOI 2410
Point cloud compression, Solid modeling, Accuracy, Fuses, Semantics, Estimation BibRef

Wang, H.X.[Hao-Xiang], Vasu, P.K.A.[Pavan Kumar Anasosalu], Faghri, F.[Fartash], Vemulapalli, R.[Raviteja], Farajtabar, M.[Mehrdad], Mehta, S.[Sachin], Rastegari, M.[Mohammad], Tuzel, O.[Oncel], Pouransari, H.[Hadi],
SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding,
LargeVM24(3635-3647)
IEEE DOI 2410
Training, Visualization, Computational modeling, Semantic segmentation, Semantics, Merging, Foundation Model, CLIP, Model Merging BibRef

An, Z.[Zhaochong], Sun, G.[Guolei], Liu, Y.[Yun], Liu, F.[Fayao], Wu, Z.[Zongwei], Wang, D.[Dan], Van Gool, L.J.[Luc J.], Belongie, S.[Serge],
Rethinking Few-shot 3D Point Cloud Semantic Segmentation,
CVPR24(3996-4006)
IEEE DOI 2410
Training, Point cloud compression, Correlation, Computational modeling, Semantic segmentation, Semantics, semantic segmentation BibRef

Wang, C.Y.[Cheng-Yao], Jiang, L.[Li], Wu, X.Y.[Xiao-Yang], Tian, Z.T.[Zhuo-Tao], Peng, B.H.[Bo-Hao], Zhao, H.S.[Heng-Shuang], Jia, J.Y.[Jia-Ya],
GroupContrast: Semantic-Aware Self-Supervised Representation Learning for 3D Understanding,
CVPR24(4917-4928)
IEEE DOI 2410
Representation learning, Point cloud compression, Semantic segmentation, Semantics, Transfer learning, Prototypes BibRef

Thomas, H.[Hugues], Tsai, Y.H.H.[Yao-Hung Hubert], Barfoot, T.D.[Timothy D.], Zhang, J.[Jian],
KPConvX: Modernizing Kernel Point Convolution with Kernel Attention,
CVPR24(5525-5535)
IEEE DOI 2410
Training, Point cloud compression, Convolutional codes, Shape, Architecture, Semantic segmentation, Deep Learning, 3D Point Cloud BibRef

Zhu, X.Y.[Xiang-Yang], Zhang, R.R.[Ren-Rui], He, B.[Bowei], Guo, Z.Y.[Zi-Yu], Liu, J.[JiaMing], Xiao, H.[Han], Fu, C.[Chaoyou], Dong, H.[Hao], Gao, P.[Peng],
No Time to Train: Empowering Non-Parametric Networks for Few-Shot 3D Scene Segmentation,
CVPR24(3838-3847)
IEEE DOI 2410
Training, Point cloud compression, Solid modeling, Filters, Semantic segmentation, Pipelines, 3D Vision, 3D Segmentation, Few-shot Learning BibRef

Xu, J.F.[Jin-Feng], Yang, S.Y.[Si-Yuan], Li, X.Z.[Xian-Zhi], Tang, Y.[Yuan], Hao, Y.X.[Yi-Xue], Hu, L.[Long], Chen, M.[Min],
PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation,
CVPR24(5977-5986)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Geometry, Knowledge engineering, Uncertainty, Semantic segmentation, Knowledge based systems, Deep learning architectures and techniques BibRef

Koch, S.[Sebastian], Vaskevicius, N.[Narunas], Colosi, M.[Mirco], Hermosilla, P.[Pedro], Ropinski, T.[Timo],
Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships,
CVPR24(14183-14193)
IEEE DOI 2410
Point cloud compression, Vocabulary, Solid modeling, Semantics, Predictive models, Graph neural networks, open-vocabulary, 3d scene understanding BibRef

Puy, G.[Gilles], Gidaris, S.[Spyros], Boulch, A.[Alexandre], Siméoni, O.[Oriane], Sautier, C.[Corentin], Pérez, P.[Patrick], Bursuc, A.[Andrei], Marlet, R.[Renaud],
Three Pillars Improving Vision Foundation Model Distillation for Lidar,
CVPR24(21519-21529)
IEEE DOI Code:
WWW Link. 2410
Laser radar, Codes, Semantic segmentation, Perturbation methods, Focusing BibRef

Yuan, Z.M.[Zhi-Min], Zeng, W.[Wankang], Su, Y.F.[Yan-Fei], Liu, W.Q.[Wei-Quan], Cheng, M.[Ming], Guo, Y.L.[Yu-Lan], Wang, C.[Cheng],
Density-guided Translator Boosts Synthetic-to-Real Unsupervised Domain Adaptive Segmentation of 3D Point Clouds,
CVPR24(23303-23312)
IEEE DOI Code:
WWW Link. 2410
Training, Point cloud compression, Bridges, Laser radar, Codes, Lidar, Unsupervised Domain Adaptation, Semantic Segmentation, DGT-ST BibRef

Mei, G.F.[Guo-Feng], Riz, L.[Luigi], Wang, Y.M.[Yi-Ming], Poiesi, F.[Fabio],
Geometrically-Driven Aggregation for Zero-Shot 3D Point Cloud Understanding,
CVPR24(27896-27905)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Solid modeling, Codes, Semantic segmentation, Semantics, training free, point cloud, aggregation BibRef

Li, J.A.[Jian-An], Dong, Q.[Qiulei],
Density-Guided Semi-Supervised 3D Semantic Segmentation with Dual-Space Hardness Sampling,
CVPR24(3260-3269)
IEEE DOI 2410
Point cloud compression, Annotations, Semantic segmentation, Semantics, Contrastive learning, Point Cloud Segmentation, Semi-supervised Learning BibRef

Li, G.R.[Guang-Rui],
Construct to Associate: Cooperative Context Learning for Domain Adaptive Point Cloud Segmentation,
CVPR24(27917-27926)
IEEE DOI 2410
Point cloud compression, Laser radar, Semantic segmentation, Noise, Prototypes, Modulation, Domain Adaptation, Transfer Learning, Point Cloud Semantic Segmentation BibRef

Cong, W.[Wenyan], Liang, H.[Hanxue], Fan, Z.W.[Zhi-Wen], Wang, P.H.[Pei-Hao], Jiang, Y.F.[Yi-Fan], Xu, D.[Dejia], Oztireli, A.C.[A. Cengiz], Wang, Z.Y.[Zhang-Yang],
NeRF as Pretraining at Scale: Generalizable 3D-Aware Semantic Representation Learning from View Prediction,
NRend24(2872-2882)
IEEE DOI 2410
Training, Representation learning, Semantic segmentation, Semantics, Estimation, Generalizable NeRF, Large-scale Pretraining, Representation Learning BibRef

Kang, X.[Xin], Chu, L.[Lei], Li, J.H.[Jia-Hao], Chen, X.J.[Xue-Jin], Lu, Y.[Yan],
Hierarchical Intra-Modal Correlation Learning for Label-Free 3D Semantic Segmentation,
CVPR24(28244-28253)
IEEE DOI 2410
Training, Visualization, Solid modeling, Correlation, Semantic segmentation BibRef

Li, R.[Rong], Li, S.J.[Shi-Jie], Chen, X.[Xieyuanli], Ma, T.[Teli], Gall, J.[Juergen], Liang, J.W.[Jun-Wei],
TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentation,
WAD24(4547-4556)
IEEE DOI 2410
Training, Laser radar, Image resolution, Semantic segmentation, Face recognition, Neural networks, LiDAR semantic segmentation, BibRef

Melekhov, I.[Iaroslav], Umashankar, A.[Anand], Kim, H.J.[Hyeong-Jin], Serkov, V.[Vladislav], Argyle, D.[Dusty],
ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic Segmentation,
UrbanModel24(7627-7637)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Laser radar, Uncertainty, Annotations, Statistical analysis, Semantic segmentation, minkowski engine BibRef

Du, S.Q.[Si-Qi], Wang, W.X.[Wei-Xi], Guo, R.Z.[Ren-Zhong], Wang, R.S.[Rui-Sheng], Tang, S.J.[Sheng-Jun],
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic Segmentation,
UrbanModel24(7608-7615)
IEEE DOI Code:
WWW Link. 2410
Representation learning, Accuracy, Quantization (signal), Fuses, Semantic segmentation, Computational modeling, Redundancy, Multi-Modal Representation Learning BibRef

Kolbeinsson, B.[Benedikt], Mikolajczyk, K.[Krystian],
DDOS: The Drone Depth and Obstacle Segmentation Dataset,
VDU24(7328-7337)
IEEE DOI 2410
Measurement, Training, Navigation, Semantic segmentation, Wires, Estimation, drones, UAV, semantic segmentation, depth estimation, dataset BibRef

Michele, B.[Björn], Boulch, A.[Alexandre], Puy, G.[Gilles], Vu, T.H.[Tuan-Hung], Marlet, R.[Renaud], Courty, N.[Nicolas],
SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation,
3DV24(421-431)
IEEE DOI 2408
Adaptation models, Surface reconstruction, Laser radar, Semantic segmentation, Data models, Proposals, Domain Adaptation, Automotive BibRef

Qian, G.C.[Guo-Cheng], Hamdi, A.[Abdullah], Zhang, X.[Xingdi], Ghanem, B.[Bernard],
Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding,
3DV24(1280-1290)
IEEE DOI Code:
WWW Link. 2408
Point cloud compression, Training, Semantic segmentation, Pipelines, Training data, Transformers, Point Cloud Classification BibRef

Wang, Y.S.[Yun-Song], Zhao, N.[Na], Lee, G.H.[Gim Hee],
Enhancing Generalizability of Representation Learning for Data-Efficient 3D Scene Understanding,
3DV24(158-168)
IEEE DOI 2408
Representation learning, Geometry, Solid modeling, Semantic segmentation, Object detection, Data models, 3D Semantic Segmentation BibRef

Mao, Y.Q.[Yong-Qiang], Guo, Z.[Zonghao], LU, X.N.[Xiao-Nan], Yuan, Z.Q.[Zhi-Qiang], Guo, H.[Haowen],
Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes,
3DV22(505-514)
IEEE DOI 2408
Point cloud compression, Measurement, Semantic segmentation, Aggregates, Semantics, Prototypes, Few shot learning, Few shot Segmentation BibRef

Wu, Z.W.[Zong-Wei], Gobichettipalayam, S.[Shriarulmozhivarman], Tamadazte, B.[Brahim], Allibert, G.[Guillaume], Paudel, D.P.[Danda Pani], Demonceaux, C.[Cédric],
Robust RGB-D Fusion for Saliency Detection,
3DV22(403-413)
IEEE DOI Code:
WWW Link. 2408
Fuses, Source coding, Semantic segmentation, Aggregates, Object detection, Benchmark testing BibRef

Du, S.L.[Sheng-Lan], Ibrahimli, N.[Nail], Stoter, J.[Jantien], Kooij, J.[Julian], Nan, L.L.[Liang-Liang],
Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds,
3DV22(1-10)
IEEE DOI Code:
WWW Link. 2408
Point cloud compression, Location awareness, Semantic segmentation, Semantics, Self-supervised learning, Encoding BibRef

Akwensi, P.H.[Perpertual Hope], Wang, R.S.[Rui-Sheng],
A Reversible Transformer for LiDAR Point Cloud Semantic Segmentation,
CRV23(19-28)
IEEE DOI 2406
Point cloud compression, Adaptation models, Computational modeling, Memory management, Benchmark testing, semantic segmentation BibRef

Guttikonda, S.[Suresh], Rambach, J.[Jason],
Single Frame Semantic Segmentation Using Multi-Modal Spherical Images,
WACV24(3210-3219)
IEEE DOI 2404
Laser radar, Deformation, Semantic segmentation, Merging, Computer architecture, Distortion, Algorithms, 3D computer vision BibRef

Shvets, M.[Mykhailo], Zhao, D.X.[Dong-Xu], Niethammer, M.[Marc], Sengupta, R.[Roni], Berg, A.C.[Alexander C.],
Joint Depth Prediction and Semantic Segmentation with Multi-View SAM,
WACV24(1317-1327)
IEEE DOI 2404
Semantic segmentation, Semantics, Estimation, Predictive models, Multitasking, Transformers, Algorithms, 3D computer vision BibRef

Unal, O.[Ozan], Dai, D.X.[Deng-Xin], Hoyer, L.[Lukas], Can, Y.B.[Yigit Baran], Van Gool, L.J.[Luc J.],
2D Feature Distillation for Weakly- and Semi-Supervised 3D Semantic Segmentation,
WACV24(7321-7330)
IEEE DOI 2404
Training, Image sensors, Laser radar, Annotations, Semantic segmentation, Semantics, Applications, Autonomous Driving, Remote Sensing BibRef

Liu, J.X.[Jia-Xu], Yu, Z.[Zhengdi], Breckon, T.P.[Toby P.], Shum, H.P.H.[Hubert P. H.],
U3DS3: Unsupervised 3D Semantic Scene Segmentation,
WACV24(3747-3756)
IEEE DOI 2404
Point cloud compression, Training, Representation learning, Solid modeling, Semantics, Algorithms, 3D computer vision, Image recognition and understanding BibRef

Tran, A.T.[Anh-Thuan], Le, H.S.[Hoanh-Su], Lee, S.H.[Suk-Hwan], Kwon, K.R.[Ki-Ryong],
PointCT: Point Central Transformer Network for Weakly-supervised Point Cloud Semantic Segmentation,
WACV24(3544-3553)
IEEE DOI 2404
Point cloud compression, Annotations, Semantic segmentation, Noise, Transformers, Algorithms, 3D computer vision BibRef

Rahman, M.A.[Md Awsafur], Fattah, S.A.[Shaikh Anowarul],
Semi-Supervised Semantic Depth Estimation using Symbiotic Transformer and NearFarMix Augmentation,
WACV24(249-258)
IEEE DOI 2404
Symbiosis, Semantics, Merging, Information sharing, Estimation, Computer architecture, Algorithms BibRef

Rizzoli, G.[Giulia], Shenaj, D.[Donald], Zanuttigh, P.[Pietro],
Source-Free Domain Adaptation for RGB-D Semantic Segmentation with Vision Transformers,
Pretrain24(607-616)
IEEE DOI 2404
Adaptation models, Image color analysis, Semantic segmentation, Semantics, Transformers, Feature extraction, Data models BibRef

Carós, M.[Mariona], Just, A.[Ariadna], Seguí, S.[Santi], Vitriŕ, J.[Jordi],
Self-Supervised Pre-Training Boosts Semantic Scene Segmentation on LiDAR data,
MVA23(1-6)
DOI Link 2403
Point cloud compression, Laser radar, Semantic segmentation, Semantics, Supervised learning, Object segmentation BibRef

Qian, R.[Rui], Ding, S.[Shuangrui], Liu, X.[Xian], Lin, D.[Dahua],
Semantics Meets Temporal Correspondence: Self-supervised Object-centric Learning in Videos,
ICCV23(16629-16641)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, M.[Miaoyu], Zhang, Y.[Yachao], Ma, X.[Xu], Qu, Y.[Yanyun], Fu, Y.[Yun],
BEV-DG: Cross-Modal Learning under Bird's-Eye View for Domain Generalization of 3D Semantic Segmentation,
ICCV23(11598-11608)
IEEE DOI 2401
BibRef

Abdelreheem, A.[Ahmed], Skorokhodov, I.[Ivan], Ovsjanikov, M.[Maks], Wonka, P.[Peter],
SATR: Zero-Shot Semantic Segmentation of 3D Shapes,
ICCV23(15120-15133)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xiang, P.[Peng], Wen, X.[Xin], Liu, Y.S.[Yu-Shen], Zhang, H.[Hui], Fang, Y.[Yi], Han, Z.Z.[Zhi-Zhong],
Retro-FPN: Retrospective Feature Pyramid Network for Point Cloud Semantic Segmentation,
ICCV23(17780-17792)
IEEE DOI Code:
WWW Link. 2401
BibRef

Sanchez, J.[Jules], Deschaud, J.E.[Jean-Emmanuel], Goulette, F.[François],
Domain generalization of 3D semantic segmentation in autonomous driving,
ICCV23(18031-18041)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xu, Z.Y.[Zong-Yi], Yuan, B.[Bo], Zhao, S.S.[Shan-Shan], Zhang, Q.N.[Qian-Ni], Gao, X.B.[Xin-Bo],
Hierarchical Point-Based Active Learning for Semi-Supervised Point Cloud Semantic Segmentation,
ICCV23(18052-18062)
IEEE DOI Code:
WWW Link. 2401
BibRef

Koo, I.[Inyong], Lee, I.[Inyoung], Kim, S.H.[Se-Ho], Kim, H.S.[Hee-Seon], Jeon, W.J.[Woo-Jin], Kim, C.[Changick],
PG-RCNN: Semantic Surface Point Generation for 3D Object Detection,
ICCV23(18096-18105)
IEEE DOI Code:
WWW Link. 2401
BibRef

Liu, L.Z.[Li-Zhao], Zhuang, Z.W.[Zhuang-Wei], Huang, S.X.[Shang-Xin], Xiao, X.L.[Xun-Long], Xiang, T.H.[Tian-Hang], Chen, C.[Cen], Wang, J.D.[Jing-Dong], Tan, M.K.[Ming-Kui],
CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation,
ICCV23(18367-18376)
IEEE DOI 2401
BibRef

Samet, N.[Nermin], Siméoni, O.[Oriane], Puy, G.[Gilles], Ponimatkin, G.[Georgy], Marlet, R.[Renaud], Lepetit, V.[Vincent],
You Never Get a Second Chance To Make a Good First Impression: Seeding Active Learning for 3D Semantic Segmentation,
ICCV23(18399-18411)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yang, Z.[Ze], Li, R.[Ruibo], Ling, E.[Evan], Zhang, C.[Chi], Wang, Y.M.[Yi-Ming], Huang, D.[Dezhao], Ma, K.T.[Keng Teck], Hur, M.[Minhoe], Lin, G.S.[Guo-Sheng],
Label-Guided Knowledge Distillation for Continual Semantic Segmentation on 2D Images and 3D Point Clouds,
ICCV23(18555-18566)
IEEE DOI Code:
WWW Link. 2401
BibRef

Cao, H.Z.[Hao-Zhi], Xu, Y.C.[Yue-Cong], Yang, J.F.[Jian-Fei], Yin, P.Y.[Peng-Yu], Yuan, S.[Shenghai], Xie, L.H.[Li-Hua],
Multi-Modal Continual Test-Time Adaptation for 3D Semantic Segmentation,
ICCV23(18763-18773)
IEEE DOI Code:
WWW Link. 2401
BibRef

Puy, G.[Gilles], Boulch, A.[Alexandre], Marlet, R.[Renaud],
Using a Waffle Iron for Automotive Point Cloud Semantic Segmentation,
ICCV23(3356-3366)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, E.[Enxu], Casas, S.[Sergio], Urtasun, R.[Raquel],
MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memory,
ICCV23(745-754)
IEEE DOI Code:
WWW Link. 2401
BibRef

Saltori, C.[Cristiano], Ošep, A.[Aljoša], Ricci, E.[Elisa], Leal-Taixé, L.[Laura],
Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation,
ICCV23(196-206)
IEEE DOI 2401
BibRef

Chen, Z.S.[Zi-Sheng], Xu, H.B.[Hong-Bin], Chen, W.T.[Wei-Tao], Zhou, Z.P.[Zhi-Peng], Xiao, H.[Haihong], Sun, B.[Baigui], Xie, X.[Xuansong], Kang, W.X.[Wen-Xiong],
PointDC: Unsupervised Semantic Segmentation of 3D Point Clouds via Cross-modal Distillation and Super-Voxel Clustering,
ICCV23(14244-14253)
IEEE DOI 2401
BibRef

Zhou, J.J.[Jun-Jie], Xiong, Y.P.[Yong-Ping], Chiu, C.[Chinwai], Liu, F.Y.[Fang-Yu], Gong, X.Y.[Xiang-Yang],
Fat: Field-Aware Transformer for 3D Point Cloud Semantic Segmentation,
ICIP23(660-664)
IEEE DOI 2312
BibRef

Royen, R.[Remco], Munteanu, A.[Adrian],
RESSCAL3D: Resolution Scalable 3D Semantic Segmentation of Point Clouds,
ICIP23(2775-2779)
IEEE DOI 2312
BibRef

Shamsafar, F.[Faranak], Jaiswal, S.I.[Sun-Il], Kelkel, B.[Benjamin], Bodduna, K.[Kireeti], Illgner-Fehns, K.[Klaus],
Leveraging Multi-view Data for Improved Detection Performance: An Industrial Use Case,
VISION23(4464-4471)
IEEE DOI 2309
BibRef

Wang, S.[Song], Li, W.[Wentong], Liu, W.Y.[Wen-Yu], Liu, X.L.[Xiao-Lu], Zhu, J.[Jianke],
LiDAR2Map: In Defense of LiDAR-Based Semantic Map Construction Using Online Camera Distillation,
CVPR23(5186-5195)
IEEE DOI 2309
BibRef

Li, J.[Jinyu], Luo, C.X.[Chen-Xu], Yang, X.D.[Xiao-Dong],
PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds,
CVPR23(17567-17576)
IEEE DOI 2309
BibRef

Yang, Y.W.[Yu-Wei], Hayat, M.[Munawar], Jin, Z.[Zhao], Zhu, H.Y.[Hong-Yuan], Lei, Y.J.[Yig-Jie],
Zero-Shot Point Cloud Segmentation by Semantic-Visual Aware Synthesis,
ICCV23(11552-11562)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yang, Y.W.[Yu-Wei], Hayat, M.[Munawar], Jin, Z.[Zhao], Ren, C.[Chao], Lei, Y.J.[Yig-Jie],
Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation,
CVPR23(21759-21768)
IEEE DOI 2309
BibRef

Zhang, Z.H.[Zi-Hui], Yang, B.[Bo], Wang, B.[Bing], Li, B.[Bo],
GrowSP: Unsupervised Semantic Segmentation of 3D Point Clouds,
CVPR23(17619-17629)
IEEE DOI 2309
BibRef

Kim, H.[Hyeonseong], Kang, Y.[Yoonsu], Oh, C.G.[Chang-Gyoon], Yoon, K.J.[Kuk-Jin],
Single Domain Generalization for LiDAR Semantic Segmentation,
CVPR23(17587-17598)
IEEE DOI 2309
BibRef

Li, J.A.[Jian-An], Dong, Q.[Qiulei],
Open-set Semantic Segmentation for Point Clouds via Adversarial Prototype Framework,
CVPR23(9425-9434)
IEEE DOI 2309
BibRef

Ding, D.Z.[Dai-Zong], Jiang, E.[Erling], Huang, Y.M.[Yuan-Min], Zhang, M.[Mi], Li, W.X.[Wen-Xuan], Yang, M.[Min],
CAP: Robust Point Cloud Classification via Semantic and Structural Modeling,
CVPR23(12260-12270)
IEEE DOI 2309
BibRef

Kong, L.D.[Ling-Dong], Ren, J.W.[Jia-Wei], Pan, L.[Liang], Liu, Z.W.[Zi-Wei],
LaserMix for Semi-Supervised LiDAR Semantic Segmentation,
CVPR23(21706-21716)
IEEE DOI 2309
BibRef

Wang, Y.Q.[Yu-Qi], Chen, Y.T.[Yun-Tao], Zhang, Z.X.[Zhao-Xiang],
FrustumFormer: Adaptive Instance-aware Resampling for Multi-view 3D Detection,
CVPR23(5096-5105)
IEEE DOI 2309
BibRef

Ando, A.[Angelika], Gidaris, S.[Spyros], Bursuc, A.[Andrei], Puy, G.[Gilles], Boulch, A.[Alexandre], Marlet, R.[Renaud],
RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving,
CVPR23(5240-5250)
IEEE DOI 2309
BibRef

Jameela, M.[Maryam], Sohn, G.[Gunho], Yoo, S.[Sunghwan],
Fusion-SUNet: Spatial Layout Consistency for 3D Semantic Segmentation,
PCV23(6568-6576)
IEEE DOI 2309
BibRef

Yoo, S.[Sunghwan], Jeong, Y.[Yeonjeong], Jameela, M.[Maryam], Sohn, G.[Gunho],
Human Vision Based 3D Point Cloud Semantic Segmentation of Large-Scale Outdoor Scenes,
PCV23(6577-6586)
IEEE DOI 2309
BibRef

Riz, L.[Luigi], Saltori, C.[Cristiano], Ricci, E.[Elisa], Poiesi, F.[Fabio],
Novel Class Discovery for 3D Point Cloud Semantic Segmentation,
CVPR23(9393-9402)
IEEE DOI 2309
BibRef

Xiao, A.[Aoran], Huang, J.X.[Jia-Xing], Xuan, W.H.[Wei-Hao], Ren, R.J.[Rui-Jie], Liu, K.[Kangcheng], Guan, D.[Dayan], El Saddik, A.[Abdulmotaleb], Lu, S.J.[Shi-Jian], Xing, E.[Eric],
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds,
CVPR23(9382-9392)
IEEE DOI 2309
BibRef

Liu, J.[Jiahui], Chang, C.[Chirui], Liu, J.H.[Jian-Hui], Wu, X.Y.[Xiao-Yang], Ma, L.[Lan], Qi, X.J.[Xiao-Juan],
MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds,
CVPR23(9372-9381)
IEEE DOI 2309
BibRef

Ryu, K.[Kwonyoung], Hwang, S.[Soonmin], Park, J.[Jaesik],
Instant Domain Augmentation for LiDAR Semantic Segmentation,
CVPR23(9350-9360)
IEEE DOI 2309
BibRef

Li, L.[Li], Shum, H.P.H.[Hubert P. H.], Breckon, T.P.[Toby P.],
Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation,
CVPR23(9361-9371)
IEEE DOI 2309
BibRef

Lu, J.C.[Jia-Cheng], Gu, S.[Shuo], Xu, C.Z.[Cheng-Zhong], Kong, H.[Hui],
A Cylindrical Convolution Network for Dense Top-view Semantic Segmentation with Lidar Point Clouds,
ACCV22(VII:344-360).
Springer DOI 2307
BibRef

Lee, M.S.[Min Seok], Yang, S.W.[Seok Woo], Han, S.W.[Sung Won],
GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentation,
WACV23(582-591)
IEEE DOI 2302
Point cloud compression, Uncertainty, Additives, Semantic segmentation, Computer network reliability, visual reasoning BibRef

Liu, M.H.[Ming-Hua], Zhou, Y.[Yin], Qi, C.R.[Charles R.], Gong, B.Q.[Bo-Qing], Su, H.[Hao], Anguelov, D.[Dragomir],
LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds,
ECCV22(XXIX:70-89).
Springer DOI 2211
BibRef

Yi, L.[Li], Gong, B.Q.[Bo-Qing], Funkhouser, T.[Thomas],
Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds,
CVPR21(15358-15368)
IEEE DOI 2111
Training, Laser radar, Semantics, Transforms, Manuals, Sensors BibRef

Unal, O.[Ozan], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Scribble-Supervised LiDAR Semantic Segmentation,
CVPR22(2687-2697)
IEEE DOI 2210
Point cloud compression, Training, Laser radar, Codes, Annotations, Computational modeling, Segmentation, Self- semi- meta- unsupervised learning BibRef

Zhao, Y.H.[Yang-Heng], Wang, J.[Jun], Li, X.L.[Xiao-Long], Hu, Y.[Yue], Zhang, C.[Ce], Wang, Y.F.[Yan-Feng], Chen, S.H.[Si-Heng],
Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation,
CVMeta22(695-703).
Springer DOI 2304
BibRef

Bansal, N.[Nitin], Ji, P.[Pan], Yuan, J.S.[Jun-Song], Xu, Y.[Yi],
Semantics-Depth-Symbiosis: Deeply Coupled Semi-Supervised Learning of Semantics and Depth,
WACV23(5817-5828)
IEEE DOI 2302
Training, Symbiosis, Semantic segmentation, Semantics, Estimation, Performance gain BibRef

Hua, Z.W.[Zhong-Wei], Qi, L.Z.[Li-Zhe], Du, D.M.[Da-Ming], Jiang, W.X.[Wen-Xuan], Sun, Y.Q.[Yun-Quan],
Dual Attention Based Multi-scale Feature Fusion Network for Indoor RGBD Semantic Segmentation,
ICPR22(3639-3644)
IEEE DOI 2212
Image color analysis, Fuses, Semantic segmentation, Image edge detection, Semantics, Lighting, Color BibRef

Song, Y.C.[You-Cheng], Sun, Z.X.[Zheng-Xing], Wu, Y.J.[Yun-Jie], Sun, Y.H.[Yun-Han], Luo, S.T.[Shou-Tong], Li, Q.[Qian],
Learning Semantic Segmentation on Unlabeled Real-World Indoor Point Clouds via Synthetic Data,
ICPR22(3750-3756)
IEEE DOI 2212
Point cloud compression, Deep learning, Adaptation models, Costs, Semantic segmentation, Semantics BibRef

Cen, J.[Jun], Yun, P.[Peng], Zhang, S.W.[Shi-Wei], Cai, J.H.[Jun-Hao], Luan, D.[Di], Tang, M.Q.[Ming-Qian], Liu, M.[Ming], Wang, M.Y.[Michael Yu],
Open-world Semantic Segmentation for LIDAR Point Clouds,
ECCV22(XXXVIII:318-334).
Springer DOI 2211
BibRef

Hu, Z.[Zeyu], Bai, X.Y.[Xu-Yang], Zhang, R.[Runze], Wang, X.[Xin], Sun, G.Y.[Guang-Yuan], Fu, H.B.[Hong-Bo], Tai, C.L.[Chiew-Lan],
LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation,
ECCV22(XXVII:248-265).
Springer DOI 2211
BibRef

Ding, R.[Runyu], Yang, J.[Jihan], Jiang, L.[Li], Qi, X.J.[Xiao-Juan],
DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation,
ECCV22(XXVII:284-303).
Springer DOI 2211
BibRef

Li, J.[Jiale], Dai, H.[Hang], Ding, Y.[Yong],
Self-Distillation for Robust LiDAR Semantic Segmentation in Autonomous Driving,
ECCV22(XXVIII:659-676).
Springer DOI 2211
BibRef

Yan, X.[Xu], Gao, J.T.[Jian-Tao], Zheng, C.[Chaoda], Zheng, C.[Chao], Zhang, R.M.[Rui-Mao], Cui, S.G.[Shu-Guang], Li, Z.[Zhen],
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds,
ECCV22(XXVIII:677-695).
Springer DOI 2211
BibRef

Ergül, M.[Mustafa], Alatan, A.[Aydin],
Depth is all you Need: Single-Stage Weakly Supervised Semantic Segmentation From Image-Level Supervision,
ICIP22(4233-4237)
IEEE DOI 2211
Training, Solid modeling, Machine vision, Semantics, Pipelines, Estimation, Semantic segmentation, Weakly supervision, Depth, Self supervision BibRef

Thyagharajan, A.[Anirud], Ummenhofer, B.[Benjamin], Laddha, P.[Prashant], Omer, O.J.[Om Ji], Subramoney, S.[Sreenivas],
Segment-Fusion: Hierarchical Context Fusion for Robust 3D Semantic Segmentation,
CVPR22(1226-1235)
IEEE DOI 2210
Solid modeling, Fuses, Computational modeling, Semantics, Network architecture, Segmentation, Scene analysis and understanding BibRef

Shin, I.[Inkyu], Tsai, Y.H.[Yi-Hsuan], Zhuang, B.B.[Bing-Bing], Schulter, S.[Samuel], Liu, B.[Buyu], Garg, S.[Sparsh], Kweon, I.S.[In So], Yoon, K.J.[Kuk-Jin],
MM-TTA: Multi-Modal Test-Time Adaptation for 3D Semantic Segmentation,
CVPR22(16907-16916)
IEEE DOI 2210
Adaptation models, Semantics, Benchmark testing, Data models, Scene analysis and understanding BibRef

Yen, Y.T.[Yu-Ting], Lu, C.N.[Chia-Ni], Chiu, W.C.[Wei-Chen], Tsai, Y.H.[Yi-Hsuan],
3D-PL: Domain Adaptive Depth Estimation with 3D-Aware Pseudo-Labeling,
ECCV22(XXVII:710-728).
Springer DOI 2211
BibRef

Robert, D.[Damien], Vallet, B.[Bruno], Landrieu, L.[Loic],
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation,
CVPR22(5565-5574)
IEEE DOI 2210
Point cloud compression, Image sensors, Image segmentation, Solid modeling, Image analysis, Semantics, Scene analysis and understanding BibRef

Hou, Y.N.[Yue-Nan], Zhu, X.G.[Xin-Ge], Ma, Y.X.[Yue-Xin], Loy, C.C.[Chen Change], Li, Y.K.[Yi-Kang],
Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation,
CVPR22(8469-8478)
IEEE DOI 2210
Point cloud compression, Solid modeling, Analytical models, Laser radar, Shape, Computational modeling, grouping and shape analysis BibRef

Zhou, Y.S.[Yun-Song], Zhu, H.Z.[Hong-Zi], Li, C.Q.[Chun-Qin], Cui, T.K.[Tian-Kai], Chang, S.[Shan], Guo, M.[Minyi],
TempNet: Online Semantic Segmentation on Large-scale Point Cloud Series,
ICCV21(7098-7107)
IEEE DOI 2203
Point cloud compression, Computational modeling, Semantics, Time series analysis, Feature extraction, Propagation losses, BibRef

Wu, T.H.[Tsung-Han], Liu, Y.C.[Yueh-Cheng], Huang, Y.K.[Yu-Kai], Lee, H.Y.[Hsin-Ying], Su, H.T.[Hung-Ting], Huang, P.C.[Ping-Chia], Hsu, W.H.[Winston H.],
ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation,
ICCV21(15490-15499)
IEEE DOI 2203
Deep learning, Point cloud compression, Annotations, Semantics, Supervised learning, Manuals, Scene analysis and understanding, Vision for robotics and autonomous vehicles BibRef

Jiang, H.Y.[Hai-Yong], Cai, J.F.[Jian-Fei], Zheng, J.M.[Jian-Min], Xiao, J.[Jun],
Neighborhood-based Neural Implicit Reconstruction from Point Clouds,
3DV21(1259-1268)
IEEE DOI 2201
Geometry, Point cloud compression, Surface reconstruction, Solid modeling, Shape, Semantics, Implicit surface, point cloud, 3D reconstruction BibRef

Zhang, T.F.[Tong-Feng], Yang, K.Z.[Kai-Zhi], Chen, X.J.[Xue-Jin],
Learning Scale-Adaptive Representations for Point-Level LiDAR Semantic Segmentation,
3DV21(920-929)
IEEE DOI 2201
Point cloud compression, Laser radar, Quantization (signal), Fuses, Semantics, Memory management, LiDAR semantic segmentation, local point refine BibRef

Michele, B.[Björn], Boulch, A.[Alexandre], Puy, G.[Gilles], Bucher, M.[Maxime], Marlet, R.[Renaud],
Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Clouds,
3DV21(992-1002)
IEEE DOI 2201
Point cloud compression, Image segmentation, Semantics, Merging, Benchmark testing, Task analysis, Zero-Shot learning, Point cloud, Transfer learning BibRef

Genova, K.[Kyle], Yin, X.Q.[Xiao-Qi], Kundu, A.[Abhijit], Pantofaru, C.[Caroline], Cole, F.[Forrester], Sud, A.[Avneesh], Brewington, B.[Brian], Shucker, B.[Brian], Funkhouser, T.[Thomas],
Learning 3D Semantic Segmentation with only 2D Image Supervision,
3DV21(361-372)
IEEE DOI 2201
Training, Image segmentation, Solid modeling, Laser radar, Semantics, Urban areas, 3D Semantic Segmentation, Cross modal Supervision, Sparse Voxel Convolution BibRef

Lumban-Gaol, Y.A., Chen, Z., Smit, M., Li, X., Erbasu, M.A., Verbree, E., Balado, J., Meijers, M., van der Vaart, N.,
A Comparative Study of Point Clouds Semantic Segmentation Using Three Different Neural Networks on the Railway Station Dataset,
ISPRS21(B3-2021: 223-228).
DOI Link 2201
BibRef

Balado, J., van Oosterom, P., Díaz-Vilarińo, L., Arias, P.,
Semantic Segmentation of Mobile Laser Scanning Point Clouds with Long Short-term Memory Networks: Preliminary Results,
ISPRS21(B2-2021: 123-130).
DOI Link 2201
BibRef

Li, L.X.[Lan-Xiao], Heizmann, M.[Michael],
A Closer Look at Invariances in Self-supervised Pre-training for 3D Vision,
ECCV22(XXX:656-673).
Springer DOI 2211
BibRef

Heide, N.F.[Nina Felicitas], Müller, E.[Erik], Petereit, J.[Janko], Heizmann, M.[Michael],
X3SEG: Model-Agnostic Explanations for the Semantic Segmentation of 3D Point Clouds With Prototypes and Criticism,
ICIP21(3687-3691)
IEEE DOI 2201
Solid modeling, Image segmentation, Databases, Semantics, Prototypes, Explainable Artificial Intelligence, Semantic segmentation, Autonomous systems BibRef

Katrolia, J.S.[Jigyasa Singh], Krämer, L.[Lars], Rambach, J.[Jason], Mirbach, B.[Bruno], Stricker, D.[Didier],
Semantic Segmentation in Depth Data: A Comparative Evaluation of Image and Point Cloud Based Methods,
ICIP21(649-653)
IEEE DOI 2201
Image segmentation, Runtime, Semantics, Training data, Computational efficiency, scene segmentation, depth image, point cloud BibRef

Li, Y.Y.[Yu-Yan], Duan, Y.[Ye],
Multi-scale Network with Attentional Multi-resolution Fusion for Point Cloud Semantic Segmentation,
ICPR22(3980-3986)
IEEE DOI 2212
Point cloud compression, Correlation, Shape, Fuses, Convolution, Semantic segmentation, Aggregates BibRef

Wang, X.[Xu], Li, Y.Y.[Yu-Yan], Duan, Y.[Ye],
Fast Point Voxel Convolution Neural Network with Selective Feature Fusion for Point Cloud Semantic Segmentation,
ISVC21(I:319-330).
Springer DOI 2112
BibRef

Li, Y.Y.[Yu-Yan], Fan, C.M.[Chuan-Mao], Wang, X.[Xu], Duan, Y.[Ye],
SPNet: Multi-shell Kernel Convolution for Point Cloud Semantic Segmentation,
ISVC21(I:366-378).
Springer DOI 2112
BibRef

Rapoport-Lavie, M.[Meytal], Raviv, D.[Dan],
It's All Around You: Range-Guided Cylindrical Network for 3D Object Detection,
AVVision21(2992-3001)
IEEE DOI 2112
Laser radar, Data analysis, Lighting, Object detection BibRef

Xu, Y.T.[Ya-Ting], Hu, C.H.[Cong-Hui], Zhao, N.[Na], Lee, G.H.[Gim Hee],
Generalized Few-Shot Point Cloud Segmentation Via Geometric Words,
ICCV23(21449-21458)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhao, N.[Na], Chua, T.S.[Tat-Seng], Lee, G.H.[Gim Hee],
Few-shot 3D Point Cloud Semantic Segmentation,
CVPR21(8869-8878)
IEEE DOI 2111
Training, Solid modeling, Semantics, Prototypes, Training data, Data models BibRef

Qiu, S.[Shi], Anwar, S.[Saeed], Barnes, N.M.[Nick M.],
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion,
CVPR21(1757-1767)
IEEE DOI 2111
Visualization, Semantics, Object detection, Benchmark testing, Real-time systems BibRef

Hu, Q.Y.[Qing-Yong], Yang, B.[Bo], Khalid, S.[Sheikh], Xiao, W.[Wen], Trigoni, N.[Niki], Markham, A.[Andrew],
Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges,
CVPR21(4975-4985)
IEEE DOI 2111
Deep learning, Costs, Annotations, Semantics, Urban areas BibRef

Klingner, M.[Marvin], Bär, A.[Andreas], Mross, M.[Marcel], Fingscheidt, T.[Tim],
Improving Online Performance Prediction for Semantic Segmentation,
SAIAD21(1-11)
IEEE DOI 2109
Training, Laser radar, Semantics, Estimation, Virtual reality, Prediction algorithms, Decoding BibRef

Unal, O.[Ozan], Van Gool, L.J.[Luc J.], Dai, D.X.[Deng-Xin],
Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection,
WACV21(2949-2958)
IEEE DOI 2106
Location awareness, Training, Image segmentation, Semantics, Pipelines, Estimation BibRef

Alnaggar, Y.A.[Yara Ali], Afifi, M.[Mohamed], Amer, K.[Karim], ElHelw, M.[Mohamed],
Multi Projection Fusion for Real-time Semantic Segmentation of 3D LiDAR Point Clouds,
WACV21(1799-1808)
IEEE DOI 2106
Laser radar, Semantics, Real-time systems, Sensors BibRef

Zhang, Y.F.[Yi-Fei], Sidibé, D.[Désiré], Morel, O.[Olivier], Meriaudeau, F.[Fabrice],
Incorporating Depth Information into Few-Shot Semantic Segmentation,
ICPR21(3582-3588)
IEEE DOI 2105
Measurement, Image segmentation, Visualization, Image color analysis, Fuses, Semantics, Neural networks BibRef

Zhong, M.[Min], Zeng, G.[Gang],
Joint Semantic-Instance Segmentation of 3D Point Clouds: Instance Separation and Semantic Fusion,
ICPR21(6616-6623)
IEEE DOI 2105
Measurement, Fuses, Semantics BibRef

Lu, T.[Tao], Wang, L.M.[Li-Min], Wu, G.S.[Gang-Shan],
CGA-Net: Category Guided Aggregation for Point Cloud Semantic Segmentation,
CVPR21(11688-11697)
IEEE DOI 2111
Aggregates, Semantics BibRef

Sun, W.X.[Wei-Xuan], Zhang, J.[Jing], Barnes, N.M.[Nick M.],
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

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, CNN 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, 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.W.[Benjamin W.], Torr, P.H.S.[Philip H.S.],
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

Hu, Z.[Zeyu], Zhen, M.M.[Ming-Min], Bai, X.Y.[Xu-Yang], Fu, H.B.[Hong-Bo], Tai, C.L.[Chiew-Lan],
JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds,
ECCV20(XX:222-239).
Springer DOI 2011
BibRef

Zhu, S., Brazil, G., Liu, X.,
The Edge of Depth: Explicit Constraints Between Segmentation and Depth,
CVPR20(13113-13122)
IEEE DOI 2008
Semantics, Estimation, Image segmentation, Image edge detection, Cameras, Training, Hemorrhaging BibRef

Zhang, Y., Zhou, Z., David, P., Yue, X., Xi, Z., Gong, B., Foroosh, H.,
PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation,
CVPR20(9598-9607)
IEEE DOI 2008
Laser radar, Semantics, Image segmentation, Neural networks, Task analysis BibRef

Wang, L., Li, X., Fang, Y.,
Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation,
CVPR20(4503-4512)
IEEE DOI 2008
Shape, Solid modeling, Neural networks, Training, Semantics, Supervised learning BibRef

Shi, H., Lin, G., Wang, H., Hung, T., Wang, Z.,
SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds,
CVPR20(4573-4582)
IEEE DOI 2008
Semantics, Convolution, Feature extraction, Image segmentation, Task analysis, Videos BibRef

Kundu, A.[Abhijit], Yin, X.Q.[Xiao-Qi], Fathi, A.[Alireza], Ross, D.[David], Brewington, B.[Brian], Funkhouser, T.[Thomas], Pantofaru, C.[Caroline],
Virtual Multi-view Fusion for 3d Semantic Segmentation,
ECCV20(XXIV:518-535).
Springer DOI 2012
BibRef

Chen, X.K.[Xiao-Kang], Lin, K.Y.[Kwan-Yee], Wang, J.B.[Jing-Bo], Wu, W.[Wayne], Qian, C.[Chen], Li, H.S.[Hong-Sheng], Zeng, G.[Gang],
Bi-directional Cross-modality Feature Propagation with Separation-and-aggregation Gate for RGB-D Semantic Segmentation,
ECCV20(XI:561-577).
Springer DOI 2011
BibRef

Malinverni, E.S., Pierdicca, R., Paolanti, M., Martini, M., Morbidoni, C., Matrone, F., Lingua, A.,
Deep Learning for Semantic Segmentation of 3d Point Cloud,
CIPA19(735-742).
DOI Link 1912
BibRef

Chen, Y.L.[Yun-Lu], Mensink, T.[Thomas], Gavves, E.[Efstratios],
3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation,
3DV19(173-182)
IEEE DOI 1911
Convolution, Semantics, Kernel, Solid modeling, Image segmentation, local convolution BibRef

Hung, S., Lo, S., Hang, H.,
Incorporating Luminance, Depth and Color Information by a Fusion-Based Network for Semantic Segmentation,
ICIP19(2374-2378)
IEEE DOI 1910
RGB-D semantic segmentation, depth map, illuminance, fusion-based network BibRef

Xing, Y., Wang, J., Chen, X., Zeng, G.,
2.5D Convolution for RGB-D Semantic Segmentation,
ICIP19(1410-1414)
IEEE DOI 1910
RGB-D Semantic Segmentation, Convoutional Neural Networks, Geometry in CNN BibRef

Hu, X., Yang, K., Fei, L., Wang, K.,
ACNET: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation,
ICIP19(1440-1444)
IEEE DOI 1910
Attention, Complementary, RGBD semantic segmentation BibRef

Hou, J.[Ji], Dai, A.[Angela], Niessner, M.[Matthias],
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans,
CVPR19(4416-4425).
IEEE DOI 2002
BibRef

Wang, L.[Lei], Huang, Y.C.[Yu-Chun], Hou, Y.L.[Yao-Lin], 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

Robert, D.[Damien], Raguet, H.[Hugo], Landrieu, L.[Loic],
Efficient 3D Semantic Segmentation with Superpoint Transformer,
ICCV23(17149-17158)
IEEE DOI 2401
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

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

Jiang, L.[Li], Shi, S.S.[Shao-Shuai], Tian, Z.T.[Zhuo-Tao], Lai, X.[Xin], Liu, S.[Shu], Fu, C.W.[Chi-Wing], Jia, J.Y.[Jia-Ya],
Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentation,
ICCV21(6403-6412)
IEEE DOI 2203
Point cloud compression, Training, Representation learning, Solid modeling, Costs, Semantics, Stereo, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Jiang, L.[Li], Zhao, H.S.[Heng-Shuang], Liu, S.[Shu], Shen, X.Y.[Xiao-Yong], Fu, C.W.[Chi-Wing], Jia, J.Y.[Jia-Ya],
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

Dai, A.[Angela], Nießner, M.[Matthias],
3DMV: Joint 3D-Multi-view Prediction for 3D Semantic Scene Segmentation,
ECCV18(X: 458-474).
Springer DOI 1810
BibRef

Engelmann, F.[Francis], Kontogianni, T.[Theodora], Schult, J.[Jonas], Leibe, B.[Bastian],
Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds,
DeepLearn-G18(III:395-409).
Springer DOI 1905
BibRef

Piewak, F.[Florian], Pinggera, P.[Peter], Schäfer, M.[Manuel], Peter, D.[David], Schwarz, B.[Beate], Schneider, N.[Nick], Enzweiler, M.[Markus], Pfeiffer, D.[David], Zöllner, M.[Marius],
Boosting LiDAR-Based Semantic Labeling by Cross-modal Training Data Generation,
MultLearnApp18(VI:497-513).
Springer DOI 1905
BibRef

Graham, B., Engelcke, M., van der Maaten, L.[Laurens],
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks,
CVPR18(9224-9232)
IEEE DOI 1812
Convolution, Memory management, Convolutional codes, Stationary state, Semantics, Image segmentation BibRef

Thomas, H., Goulette, F., Deschaud, J., Marcotegui, B.,
Semantic Classification of 3D Point Clouds with Multiscale Spherical Neighborhoods,
3DV18(390-398)
IEEE DOI 1812
geometry, learning (artificial intelligence), nearest neighbour methods, pattern classification, Segmentation BibRef

Zhang, C., Luo, W., Urtasun, R.,
Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds,
3DV18(399-408)
IEEE DOI 1812
cameras, feature extraction, image matching, image reconstruction, learning (artificial intelligence), image reconstruction, driving BibRef

Li, Y., Zhang, J., Cheng, Y., Huang, K., Tan, T.,
Semantics-guided multi-level RGB-D feature fusion for indoor semantic segmentation,
ICIP17(1262-1266)
IEEE DOI 1803
Feature extraction, Fuses, Image segmentation, Legged locomotion, Semantics, Streaming media, Sun, Indoor semantic segmentation, RGB-D BibRef

Liu, F., Li, S., Zhang, L., Zhou, C., Ye, R., Wang, Y., Lu, J.,
3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-Scale 3D Point Clouds,
ICCV17(5679-5688)
IEEE DOI 1802
convolution, feature extraction, grammars, image classification, image segmentation, BibRef

Namin, S.R., Alvarez, J.M., Petersson, L.,
2D-3D semantic segmentation using cardinality as higher-order loss,
ICPR16(3775-3780)
IEEE DOI 1705
Image edge detection, Image segmentation, Labeling, Sensors, Training. BibRef

Wang, J.H.[Jing-Hua], Wang, Z.H.[Zhen-Hua], Tao, D.C.[Da-Cheng], See, S.[Simon], Wang, G.[Gang],
Learning Common and Specific Features for RGB-D Semantic Segmentation with Deconvolutional Networks,
ECCV16(V: 664-679).
Springer DOI 1611
BibRef

Tang, B., Zhou, Y., Yu, Y., Du, S.,
Higher-order class-specific priors for semantic segmentation of 3D outdoor scenes,
WACV16(1-9)
IEEE DOI 1606
Analytical models BibRef

Savinov, N.[Nikolay], Ladicky, L.[Lubor], Hane, C.[Christian], Pollefeys, M.[Marc],
Discrete optimization of ray potentials for semantic 3D reconstruction,
CVPR15(5511-5518)
IEEE DOI 1510
BibRef

Fooladgar, F., Kasaei, S.,
Semantic Segmentation of RGB-D Images Using 3D and Local Neighbouring Features,
DICTA15(1-7)
IEEE DOI 1603
computer vision BibRef

Banica, D.[Dan], Sminchisescu, C.[Cristian],
Second-order constrained parametric proposals and sequential search-based structured prediction for semantic segmentation in RGB-D images,
CVPR15(3517-3526)
IEEE DOI 1510
BibRef

Samrouth, K., Deforges, O., Liu, Y.[Yi], Falou, W., Khalil, M.,
A joint 3D image semantic segmentation and scalable coding scheme with ROI approach,
VCIP14(270-273)
IEEE DOI 1504
data compression BibRef

Namin, S.T.[Sarah Taghavi], Najafi, M.[Mohammad], Salzmann, M.[Mathieu], Petersson, L.[Lars],
A Multi-modal Graphical Model for Scene Analysis,
WACV15(1006-1013)
IEEE DOI 1503
Graphical models 2D-3D data. Semantic segmentation. BibRef

Deng, Z., Todorovic, S., Latecki, L.J.,
Semantic Segmentation of RGBD Images with Mutex Constraints,
ICCV15(1733-1741)
IEEE DOI 1602
Computational modeling BibRef

Kundu, A.[Abhijit], Li, Y.[Yin], Dellaert, F.[Frank], Li, F.X.[Fu-Xin], Rehg, J.M.[James M.],
Joint Semantic Segmentation and 3D Reconstruction from Monocular Video,
ECCV14(VI: 703-718).
Springer DOI 1408
BibRef

Lin, D.[Dahua], Fidler, S.[Sanja], Urtasun, R.[Raquel],
Holistic Scene Understanding for 3D Object Detection with RGBD Cameras,
ICCV13(1417-1424)
IEEE DOI 1403
BibRef

Floros, G.[Georgios], Leibe, B.[Bastian],
Joint 2D-3D temporally consistent semantic segmentation of street scenes,
CVPR12(2823-2830).
IEEE DOI 1208
BibRef

Micusik, B.[Branislav], Kosecka, J.[Jana],
Semantic segmentation of street scenes by superpixel co-occurrence and 3D geometry,
ObjectEvent09(625-632).
IEEE DOI 0910
identify as one of a few common object/background classes. BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Instance Segmentation, Point Cloud Segmentation .


Last update:Nov 26, 2024 at 16:40:19