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Regularized fully convolutional networks for RGB-D semantic
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VCIP16(1-4)
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1701
Brightness
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Zanuttigh, P.[Pietro],
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Deep depth regression, RGBD semantic segmentation,
Convolutional neural network, Fully convolutional network
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LiDAR, High-resolution imagery, Multi-modal fusion,
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1907
Point cloud, Semantic segmentation, Deep learning,
Multi-scale contextual information
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2005
Feature extraction, Convolution,
Semantics, Kernel, Correlation, Task analysis, Deep learning,
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3D Semantic segmentation, Point clouds, Feature fusion, Attention mechanism
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Elsevier DOI
2011
Point clouds, Semantic segmentation, Active learning,
Incremental learning, Deep learning
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Lin, D.[Di],
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2009
Image segmentation, Semantics, Decoding,
Image resolution, Feature extraction, Correlation, RGB-D images,
convolutional neural networks
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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
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Han, X.[Xu],
Dong, Z.[Zhen],
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PandRS(175), 2021, pp. 199-214.
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2105
Point cloud, 3D deep learning, Semantic segmentation,
Feature aggregation, Unbalanced classes
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Jiang, B.[Bo],
Zhou, Z.[Zitai],
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Tang, J.[Jin],
Luo, B.[Bin],
cmSalGAN: RGB-D Salient Object Detection With Cross-View Generative
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MultMed(23), 2021, pp. 1343-1353.
IEEE DOI
2105
Saliency detection, Feature extraction,
Object detection, Generative adversarial networks, Fuses,
Multi-view Learning
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Chen, L.Z.,
Lin, Z.,
Wang, Z.,
Yang, Y.L.,
Cheng, M.M.,
Spatial Information Guided Convolution for Real-Time RGBD Semantic
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IP(30), 2021, pp. 2313-2324.
IEEE DOI
2102
convolutional neural nets, geometry, image colour analysis,
image segmentation, stereo image processing,
RGBD semantic segmentation
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Zhang, G.D.[Guo-Dong],
Xue, J.H.[Jing-Hao],
Xie, P.W.[Peng-Wei],
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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
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Gao, Q.[Qian],
Shen, X.[Xukun],
ThickSeg: Efficient semantic segmentation of large-scale 3D point
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IVC(108), 2021, pp. 104161.
Elsevier DOI
2104
3D point cloud, Semantic segmentation,
Convolutional neural network, Large scale
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Kwak, J.[Jeonghoon],
Sung, Y.[Yunsick],
DeepLabV3-Refiner-Based Semantic Segmentation Model for Dense 3D
Point Clouds,
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2104
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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
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Liu, W.[Wei],
Luo, Z.M.[Zhi-Ming],
Cai, Y.Z.[Yuan-Zheng],
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Ke, Y.[Yang],
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Li, J.[Jonathan],
Adversarial Unsupervised Domain Adaptation for 3D Semantic
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Elsevier DOI
2106
Semantic segmentation, Point cloud, Domain adaptation,
Adversarial learning, Multi-modal learning
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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
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PandRS(176), 2021, pp. 151-168.
Elsevier DOI
2106
Point clouds, Semantic segmentation, Global context, Attention models
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Sithole, G.[George],
Vosselman, G.[George],
Experimental comparison of filter algorithms for bare-Earth extraction
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PandRS(59), No. 1-2, August 2004, pp. 85-101.
Elsevier DOI
0411
See also Bridge detection in airborne laser scanner data.
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Lin, Y.P.[Ya-Ping],
Vosselman, G.[George],
Yang, M.Y.[Michael Ying],
Weakly supervised semantic segmentation of airborne laser scanning
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PandRS(187), 2022, pp. 79-100.
Elsevier DOI
2205
Airborne laser scanning, Point clouds, Weak supervision,
Semantic segmentation, Subcloud labels
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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
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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
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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
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Lamas, D.[Daniel],
Soilán, M.[Mario],
Grandío, J.[Javier],
Riveiro, B.[Belén],
Automatic Point Cloud Semantic Segmentation of Complex Railway
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Liu, H.[Hao],
Guo, Y.L.[Yu-Lan],
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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
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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
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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],
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Trigoni, N.[Niki],
Markham, A.[Andrew],
Learning Semantic Segmentation of Large-Scale Point Clouds With
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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.[Ale],
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
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],
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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:
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2401
BibRef
Saltori, C.[Cristiano],
Oep, A.[Aljoa],
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
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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.,
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WACV16(1-9)
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CVPR15(5511-5518)
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Fooladgar, F.,
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Semantic Segmentation of RGB-D Images Using 3D and Local Neighbouring
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DICTA15(1-7)
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computer vision
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CVPR15(3517-3526)
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VCIP14(270-273)
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data compression
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WACV15(1006-1013)
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Graphical models
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Deng, Z.,
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ICCV15(1733-1741)
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Computational modeling
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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 .