11.2.4.8.1 Semantic Object Detection RGB-D Data, RGBD Data

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

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

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

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

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

Du, J.[Jing], Cai, G.R.[Guo-Rong], Wang, Z.Y.[Zong-Yue], Huang, S.F.[Shang-Feng], Su, J.H.[Jin-He], 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

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

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

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

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

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

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

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

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

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

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

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

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

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, 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

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

Lyu, J.H.[Jia-Hang], Qi, Y.Z.[Yong-Ze], You, S.[Suilian], Meng, J.[Jin], Meng, X.[Xin], Kodagoda, S.[Sarath], Wang, S.F.[Shi-Feng],
CaLiJD: Camera and LiDAR Joint Contender for 3D Object Detection,
RS(16), No. 23, 2024, pp. 4593.
DOI Link 2501
BibRef

Rao, Z.Y.[Zhong-Yu], Cai, Y.F.[Ying-Feng], Wang, H.[Hai], Chen, L.[Long], Li, Y.C.[Yi-Cheng],
A multi-stage model for bird's eye view prediction based on stereo-matching model and RGB-D semantic segmentation,
IET-ITS(18), No. 12, 2024, pp. 2552-2564.
DOI Link 2501
autonomous driving, image recognition, learning (artificial intelligence) BibRef

Wei, S.[Shuobin], Zhou, Z.[Zhuang], Lu, Z.A.[Zheng-An], Yuan, Z.Z.[Zi-Zhao], Su, B.H.[Bing-Hua],
HDBFormer: Efficient RGB-D Semantic Segmentation With a Heterogeneous Dual-Branch Framework,
SPLetters(32), 2025, pp. 91-95.
IEEE DOI 2501
Feature extraction, Transformers, Convolution, Semantic segmentation, Decoding, Kernel, Fuses, Accuracy, Training, RGB-D semantic segmentation BibRef

Xu, J.Y.[Jing-Yi], Deng, X.[Xin], Fu, Y.B.[Yi-Bing], Xu, M.[Mai], Li, S.X.[Sheng-Xi],
MDSC-Net: Multi-Modal Discriminative Sparse Coding Driven RGB-D Classification Network,
MultMed(27), 2025, pp. 442-454.
IEEE DOI 2501
Feature extraction, Image coding, Image classification, Dictionaries, Optimization, Classification algorithms, Discriminative features BibRef

Vijaywargiya, J.[Jayati], Ramiya, A.M.[Anandakumar M.],
Semantic segmentation of urban airborne LiDAR data of varying landcover diversity using XGBoost,
IET-CV(19), No. 1, 2025, pp. e12334.
DOI Link 2502
feature extraction, feature selection, laser ranging, learning (artificial intelligence), remote sensing BibRef

Bai, L.Z.[Li-Zhi], Yang, J.[Jun], Tian, C.Q.[Chun-Qi], Sun, Y.[Yaoru], Mao, M.[Maoyu], Xu, Y.J.[Yan-Jun], Xu, W.R.[Wei-Rong],
DCANet: Differential convolution attention network for RGB-D semantic segmentation,
PR(162), 2025, pp. 111379.
Elsevier DOI 2503
Semantic segmentation, RGB-D, Differential convolution, Attention 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

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

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

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

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

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

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

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

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

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

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

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