3D Graph Neural Networks for RGBD Semantic Segmentation

Deep Residual Learning for Image Recognition

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Fully convolutional networks for semantic segmentation

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Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

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FKAConv: Feature-Kernel Alignment for Point Cloud Convolution

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DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes

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Real-Time Progressive 3D Semantic Segmentation for Indoor Scenes

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HAPGN: Hierarchical Attentive Pooling Graph Network for Point Cloud Segmentation

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Inference in Probabilistic Graphical Models by Graph Neural Networks

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Learning Multi-View Interactional Skeleton Graph for Action Recognition

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Radar-PointGNN: Graph Based Object Recognition for Unstructured Radar Point-cloud Data

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Variational Context-Deformable ConvNets for Indoor Scene Parsing

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Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks

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FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation

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Accelerating large scale real-time GNN inference using channel pruning

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Applications of graph convolutional networks in computer vision

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Learning Semantics-Preserving Attention and Contextual Interaction for Group Activity Recognition

Tang, Y., Lu, J., Wang, Z., Yang, M., & Zhou, J. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2914577 · Cited by 62

Pixel Difference Convolutional Network for RGB-D Semantic Segmentation

Yang, J., Bai, L., Sun, Y., Tian, C., Mao, M., & Wang, G. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3296162 · Cited by 65

3D-to-2D Distillation for Indoor Scene Parsing

Liu, Z., Qi, X., & Fu, C. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00444 · Cited by 63

Semantic Image Segmentation: Two Decades of Research

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Using Virtual Replicas to Improve Mixed Reality Remote Collaboration

Tian, H., Lee, G., Bai, H., & Billinghurst, M. (2023) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2023.3247113 · Cited by 58

Human Pose Estimation with Spatial Contextual InformationPreprint

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Successive Graph Convolutional Network for Image De-raining

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Multi-Granularity Reasoning for Social Relation Recognition From Images

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Graph Partition Neural Networks for Semi-Supervised ClassificationPreprint

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Deep Learning Based 3D Segmentation: A SurveyPreprint

He, Y., Yu, H., Liu, X., Yang, Z., Sun, W. J., Anwar, S., & Mian, A. S. (2021) · arXiv (Cornell University) · doi:10.2139/ssrn.4824679 · Cited by 56

Rethinking Few-shot 3D Point Cloud Semantic Segmentation

An, Z., Sun, G., Liu, Y., Liu, F., Wu, Z., Wang, D., Gool, L. V., & Belongie, S. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.00383 · Cited by 54

DRNet: Dual-stage refinement network with boundary inference for RGB-D semantic segmentation of indoor scenes

Yang, E., Zhou, W., Qian, X., Lei, J., & Yu, L. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.106729 · Cited by 52

Deep learning based 3D segmentation in computer vision: A survey

He, Y., Yu, H., Liu, X., Yang, Z., Sun, W. J., Anwar, S., & Mian, A. S. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102722 · Cited by 130

A review of deep learning-based stereo vision techniques for phenotype feature and behavioral analysis of fish in aquaculture

Zhao, Y., Qin, H., Xu, L. P., Yu, H., & Chen, Y. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10960-7 · Cited by 59

Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use Cases

Guo, X., Polanía, L. F., Zhu, B., Boncelet, C., & Barner, K. E. (2020) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv45572.2020.9093547 · Cited by 51

Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds

Engelmann, F., Kontogianni, T., Schult, J., & Leibe, B. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-11015-4_29 · Cited by 50

A survey on indoor RGB-D semantic segmentation: from hand-crafted features to deep convolutional neural networks

Fooladgar, F., & Kasaei, S. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-7684-3 · Cited by 54

Cross-Sensor Deep Domain Adaptation for LiDAR Detection and Segmentation

Rist, C. B., Enzweiler, M., & Gavrila, D. M. (2019) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2019.8814047 · Cited by 49

Channel Exchanging Networks for Multimodal and Multitask Dense Image Prediction

Wang, Y., Sun, F., Huang, W., He, F., & Tao, D. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3211086 · Cited by 53

MV-GNN: Multi-View Graph Neural Network for Compression Artifacts Reduction

He, X., Liu, Q., & Yang, Y. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2994412 · Cited by 48

RGB-D Co-attention Network for Semantic Segmentation

Zhou, H., Qi, L., Wan, Z., Huang, H. Y., & Yang, X. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69525-5_31 · Cited by 48

Fuzzy Logic in Surveillance Big Video Data Analysis

Muhammad, K., Obaidat, M. S., Hussain, T., Ser, J. D., Kumar, N., Tanveer, M., & Doctor, F. (2021) · ACM Computing Surveys · doi:10.1145/3444693 · Cited by 54

Superpixel-Based Attention Graph Neural Network for Semantic Segmentation in Aerial Images

Diao, Q., Dai, Y., Zhang, C., Wu, Y. X., Feng, X., & Pan, F. (2022) · Remote Sensing · doi:10.3390/rs14020305 · Cited by 49

Structure-Coherent Deep Feature Learning for Robust Face Alignment

Lin, C., Zhu, B., Wang, Q., Liao, R., Qian, C., Lu, J., & Zhou, J. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3082319 · Cited by 47

MAAS: Multi-modal Assignation for Active Speaker Detection

Alcázar, J. L., Heilbron, F. C., Thabet, A., & Ghanem, B. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00033 · Cited by 57

A Novel Deep Learning Stack for APT Detection

Bodström, T., & Hämäläinen, T. (2019) · Applied Sciences · doi:10.3390/app9061055 · Cited by 46

An Outline of Multi-Sensor Fusion Methods for Mobile Agents Indoor Navigation

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Graph Interaction Networks for Relation Transfer in Human Activity Videos

Tang, Y.-S., Wei, Y., Yu, X.-M., Lu, J.-W., & Zhou, J. (2020) · IEEE transactions on circuits and systems for video technology (Print) · doi:10.1109/tcsvt.2020.2973301 · Cited by 38

Graph convolutional neural networks with node transition probability-based message passing and DropNode regularization

Huu, T., Nguyen, D. M., Bekoulis, G., Munteanu, A., & Deligiannis, N. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.114711 · Cited by 46

Malleable 2.5D Convolution: Learning Receptive Fields Along the Depth-Axis for RGB-D Scene Parsing

Xing, Y., Wang, J., & Zeng, G. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58529-7_33 · Cited by 45

DCANet: Differential convolution attention network for RGB-D semantic segmentation

Bai, L., Yang, J., Tian, C., Sun, Y., Mao, M., Xu, Y., & Wei-rong, X. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111379 · Cited by 44

Clinical usefulness of intrathecal injection of methylcobalamin in patients with diabetic neuropathy.

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Efficient Graph Convolution for Joint Node Representation Learning and Clustering

Fettal, C., Labiod, L., & Nadif, M. (2022) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3488560.3498533 · Cited by 44

Graph neural network-based fault diagnosis: a reviewPreprint

Chen, Z., Xu, J., Alippi, C., Ding, S. X., Shardt, Y. A. W., Peng, T., & Yang, C. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.08185 · Cited by 82

Multiscale Attention Fusion Graph Network for Remote Sensing Building Change Detection

Shangguan, Y., Li, J., Chen, Z., Ren, L., & Hua, Z. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3356711 · Cited by 42

Targeted Sentiment Classification Based on Attentional Encoding and Graph Convolutional Networks

Xiao, L., Hu, X., Chen, Y., Xue, Y., Gu, D., Chen, B., & Zhang, T. (2020) · Applied Sciences · doi:10.3390/app10030957 · Cited by 42

Composing Good Shots by Exploiting Mutual Relations

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Group Re-Identification With Group Context Graph Neural Networks

Zhu, J., Yang, H., Lin, W., Liu, N., Wang, J., & Zhang, W. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3013531 · Cited by 44

HSGAN: Hierarchical Graph Learning for Point Cloud Generation

Li, Y., & Baciu, G. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3073318 · Cited by 42

When Pansharpening Meets Graph Convolution Network and Knowledge Distillation

Yan, K., Zhou, M., Liu, L., Xie, C., & Hong, D. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3168192 · Cited by 42

Image Co-Saliency Detection and Instance Co-Segmentation Using Attention Graph Clustering Based Graph Convolutional Network

Li, T., Zhang, K., Shen, S., Liu, B., Liu, Q., & Li, Z. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3054526 · Cited by 42

Hard pixel mining for depth privileged semantic segmentation

Gu, Z., Niu, L., Zhao, H., & Zhang, L. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3035231 · Cited by 41

Semantics-guided reconstruction of indoor navigation elements from 3D colorized points

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Active Scene Understanding via Online Semantic Reconstruction

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Meta-Aggregator: Learning to Aggregate for 1-bit Graph Neural Networks

Jing, Y., Yang, Y., Wang, X., Song, M., & Tao, D. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00525 · Cited by 38

Dynamic Graph-Level Neural Network for SAR Image Change Detection

Wang, R., Wang, L., Wei, X., Chen, J., & Jiao, L. (2021) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2021.3132167 · Cited by 37

Interaction Transformer for Human Reaction Generation

Chopin, B., Tang, H., Otberdout, N., Daoudi, M., & Sebe, N. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3242152 · Cited by 49

Introduction to Graph Neural Networks

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2.5D Convolution for RGB-D Semantic Segmentation

Xing, Y., Wang, J., Chen, X., & Zeng, G. (2019) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2019.8803757 · Cited by 35

CMANet: Cross-Modality Attention Network for Indoor-Scene Semantic Segmentation

Zhu, L., Kang, Z., Zhou, M., Yang, X. C., Wang, Z., Cao, Z., & Ye, C. (2022) · Sensors · doi:10.3390/s22218520 · Cited by 36

SG-GAN: Adversarial Self-Attention GCN for Point Cloud Topological Parts Generation

Li, Y., & Baciu, G. (2021) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2021.3069195 · Cited by 34

Graph Neural Networks in Point Clouds: A Survey

Li, D., Lu, C., Chen, Z., Guan, J., Zhao, J., & Du, J. (2024) · Remote Sensing · doi:10.3390/rs16142518 · Cited by 36

Zig-Zag Network for Semantic Segmentation of RGB-D Images

Lin, D., & Huang, H. F. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2923513 · Cited by 34

Learning Geocentric Object Pose in Oblique Monocular Images

Christie, G. A., Abujder, R. R. R. M., Foster, K., Hagstrom, S., Hager, G. D., & Brown, M. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01452 · Cited by 34

Feature Contrast Difference and Enhanced Network for RGB-D Indoor Scene Classification in Internet of Things

Zhou, W., Jian, B., & Liu, Y. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3537281 · Cited by 33

Sparse-to-Dense Depth Completion Revisited: Sampling Strategy and Graph Construction

Xiong, X., Xiong, H., Xian, K., Zhao, C., Cao, Z., & Li, X. S. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58589-1_41 · Cited by 33

CMPFFNet: Cross-Modal and Progressive Feature Fusion Network for RGB-D Indoor Scene Semantic Segmentation

Zhou, W., Xiao, Y., Yan, W., & Yu, L. (2023) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2023.3313122 · Cited by 31

Semantic RGB-D SLAM for Rescue Robot Navigation

Deng, W., Huang, K., Chen, X., Zhou, Z., Shi, C., Guo, R., & Zhang, H. (2020) · IEEE Access · doi:10.1109/access.2020.3031867 · Cited by 32

Adaptive Graph Adversarial Networks for Partial Domain Adaptation

Kim, Y., & Hong, S. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3056208 · Cited by 32

Coupling Two-Stream RGB-D Semantic Segmentation Network by Idempotent Mappings

Xing, Y., Wang, J. B., Chen, X., & Zeng, G. (2019) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2019.8803146 · Cited by 31

SurfConv: Bridging 3D and 2D Convolution for RGBD Images

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Community enhanced graph convolutional networks

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Efficient Point Cloud Segmentation with Geometry-Aware Sparse Networks

Ye, M., Wan, R., Xu, S., Cao, T., & Chen, Q. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19842-7_12 · Cited by 30

3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation

Chen, Y., Mensink, T., & Gavves, E. (2019) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2019.00028 · Cited by 29

CNN-Based RGB-D Salient Object Detection: Learn, Select, and Fuse

Chen, H., Li, Y., Deng, Y., & Lin, G. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-021-01452-0 · Cited by 29

DGPINet-KD: Deep Guided and Progressive Integration Network With Knowledge Distillation for RGB-D Indoor Scene Analysis

Zhou, W., Jian, B., Fang, M., Dong, X., Liu, Y., & Jiang, Q. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3382354 · Cited by 29

DPRNet: Deep 3D Point Based Residual Network for Semantic Segmentation and Classification of 3D Point Clouds

Arshad, S., Shahzad, M., Riaz, Q., & Fraz, M. M. (2019) · IEEE Access · doi:10.1109/access.2019.2918862 · Cited by 30

基于点云数据的三维目标检测技术研究进展

Jianan, 李. L., Ze, 王. W., & Ting-fa, 许. X. (2023) · Acta Optica Sinica · doi:10.3788/aos230745 · Cited by 28

CheckerPose: Progressive Dense Keypoint Localization for Object Pose Estimation with Graph Neural Network

Lian, R., & Ling, H. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01289 · Cited by 28

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

Chen, X., Liu, T., Zhao, H., Zhou, G., & Zhang, Y.-Q. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01903 · Cited by 28

Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack LearningPreprint

Si, C., Jing, Y., Wang, W., Wang, L., & Tan, T. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.02335 · Cited by 37

SGA-Net: Self-Constructing Graph Attention Neural Network for Semantic Segmentation of Remote Sensing Images

Zi, W., Xiong, W., Chen, H., Li, J., & Jing, N. (2021) · Remote Sensing · doi:10.3390/rs13214201 · Cited by 29

RGB-D Gate-guided edge distillation for indoor semantic segmentation

Zou, W., Peng, Y., Zhang, Z., Tian, S., & Li, X. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11395-w · Cited by 27

Node Representation Learning in Graph via Node-to-Neighbourhood Mutual Information Maximization

Dong, W., Wu, J., Luo, Y., Ge, Z., & Wang, P. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01612 · Cited by 29

EdgeNet: Semantic Scene Completion from a Single RGB- D Image

Dourado, A., de Campos, T. E., Kim, H., & Hilton, A. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9413252 · Cited by 27

PH-GCN: Person Retrieval With Part-Based Hierarchical Graph Convolutional Network

Jiang, B., Wang, X., Zheng, A., Tang, J., & Luo, B. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3095789 · Cited by 26

RAFNet: RGB-D attention feature fusion network for indoor semantic segmentation

Yan, X., Hou, S., Karim, A., & Jia, W. (2021) · Displays · doi:10.1016/j.displa.2021.102082 · Cited by 26

What Object Should I Use? - Task Driven Object Detection

Sawatzky, J., Souri, Y., Grund, C., & Gall, J. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00779 · Cited by 25

A Survey of Un-, Weakly-, and Semi-Supervised Learning Methods for Noisy, Missing and Partial Labels in Industrial Vision Applications

Simmler, N., Sager, P., Andermatt, P., Chavarriaga, R., Schilling, F.-P., Rosenthal, M., & Stadelmann, T. (2021) · IEEE Swiss Conference on Data Science (SDS) · doi:10.1109/sds51136.2021.00012 · Cited by 32

Spatial–Temporal Synchronous Graph Transformer network (STSGT) for COVID-19 forecasting

Banerjee, S., Dong, M., & Shi, W. (2022) · Smart Health · doi:10.1016/j.smhl.2022.100348 · Cited by 30

Link-RGBD: Cross-Guided Feature Fusion Network for RGBD Semantic Segmentation

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Multi-Modal Attention-based Fusion Model for Semantic Segmentation of RGB-Depth ImagesPreprint

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