Research Publications - Crowd Modelling

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Our Crowd Modelling Research

Individuals in a crowd interact intrinsically with each other. We model such interaction to better predict their movement trajectories, synthesise crowd behaviour, and identify anomalies.

Interested in our research? Consider joining us.

Crowd Modelling Demos

ACM SIGGRAPH 2025 - Large-Scale Multi-Character Interaction Synthesis 
ESWA 2022 - Formation Control for UAVs Using a Flux Guided Approach 
SMC 2021 - Semantics-STGCNN: A Semantics-Guided Spatial-Temporal Graph Convolutional Network for Multi-Class Trajectory Prediction 
CGF 2018 - Data-Driven Crowd Motion Control with Multi-Touch Gestures 
CGF 2016 - Coordinated Crowd Simulation with Topological Scene Analysis 
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Journal Papers

BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction
BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction  Impact Factor: 8.9† Top 25% Journal in Computer Science, Artificial Intelligence†   Citation: 21#
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025
Ruochen Li, Stamos Katsigiannis, Tae-Kyun Kim and Hubert P. H. Shum
Webpage Cite This Plain Text 
Ruochen Li, Stamos Katsigiannis, Tae-Kyun Kim and Hubert P. H. Shum, "BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction," IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 8, pp. 14566-14580, IEEE, 2025.
Bibtex 
@article{li25bpsgcn,
 author={Li, Ruochen and Katsigiannis, Stamos and Kim, Tae-Kyun and Shum, Hubert P. H.},
 journal={IEEE Transactions on Neural Networks and Learning Systems},
 title={BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction},
 year={2025},
 volume={36},
 number={8},
 pages={14566--14580},
 numpages={15},
 doi={10.1109/TNNLS.2025.3545268},
 publisher={IEEE},
}
RIS 
TY  - JOUR
AU  - Li, Ruochen
AU  - Katsigiannis, Stamos
AU  - Kim, Tae-Kyun
AU  - Shum, Hubert P. H.
T2  - IEEE Transactions on Neural Networks and Learning Systems
TI  - BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction
PY  - 2025
VL  - 36
IS  - 8
SP  - 14566
EP  - 14580
DO  - 10.1109/TNNLS.2025.3545268
PB  - IEEE
ER  - 
Paper Supplementary Material
Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction
Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction  Impact Factor: 11.1† Top 10% Journal in Engineering, Electrical & Electronic†   Citation: 39#
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2025
Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis, Zhanxing Zhu and Hubert P. H. Shum
Webpage Cite This Plain Text 
Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis, Zhanxing Zhu and Hubert P. H. Shum, "Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction," IEEE Transactions on Circuits and Systems for Video Technology, vol. 35, no. 7, pp. 7047-7060, IEEE, 2025.
Bibtex 
@article{li25unified,
 author={Li, Ruochen and Qiao, Tanqiu and Katsigiannis, Stamos and Zhu, Zhanxing and Shum, Hubert P. H.},
 journal={IEEE Transactions on Circuits and Systems for Video Technology},
 title={Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction},
 year={2025},
 volume={35},
 number={7},
 pages={7047--7060},
 numpages={14},
 doi={10.1109/TCSVT.2025.3539522},
 publisher={IEEE},
}
RIS 
TY  - JOUR
AU  - Li, Ruochen
AU  - Qiao, Tanqiu
AU  - Katsigiannis, Stamos
AU  - Zhu, Zhanxing
AU  - Shum, Hubert P. H.
T2  - IEEE Transactions on Circuits and Systems for Video Technology
TI  - Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction
PY  - 2025
VL  - 35
IS  - 7
SP  - 7047
EP  - 7060
DO  - 10.1109/TCSVT.2025.3539522
PB  - IEEE
ER  - 
Paper GitHub
Formation Control for UAVs Using a Flux Guided Approach
Formation Control for UAVs Using a Flux Guided Approach  Impact Factor: 7.5† Top 25% Journal in Computer Science, Artificial Intelligence†   Citation: 13#
Expert Systems with Applications (ESWA), 2022
John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang and Subramanian Ramamoorthy
Webpage Cite This Plain Text 
John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang and Subramanian Ramamoorthy, "Formation Control for UAVs Using a Flux Guided Approach," Expert Systems with Applications, vol. 205, pp. 117665, Elsevier, 2022.
Bibtex 
@article{hartley21formation,
 author={Hartley, John and Shum, Hubert P. H. and Ho, Edmond S. L. and Wang, He and Ramamoorthy, Subramanian},
 journal={Expert Systems with Applications},
 title={Formation Control for UAVs Using a Flux Guided Approach},
 year={2022},
 volume={205},
 pages={117665},
 numpages={11},
 doi={10.1016/j.eswa.2022.117665},
 issn={0957-4174},
 publisher={Elsevier},
}
RIS 
TY  - JOUR
AU  - Hartley, John
AU  - Shum, Hubert P. H.
AU  - Ho, Edmond S. L.
AU  - Wang, He
AU  - Ramamoorthy, Subramanian
T2  - Expert Systems with Applications
TI  - Formation Control for UAVs Using a Flux Guided Approach
PY  - 2022
VL  - 205
SP  - 117665
EP  - 117665
DO  - 10.1016/j.eswa.2022.117665
SN  - 0957-4174
PB  - Elsevier
ER  - 
Paper YouTube
PyTorch-Based Implementation of Label-Aware Graph Representation for Multi-Class Trajectory Prediction
PyTorch-Based Implementation of Label-Aware Graph Representation for Multi-Class Trajectory Prediction  Impact Factor: 1.2†    Citation: 11#
Software Impacts (SIMPAC), 2021
Qianhui Men and Hubert P. H. Shum
Webpage Cite This Plain Text 
Qianhui Men and Hubert P. H. Shum, "PyTorch-Based Implementation of Label-Aware Graph Representation for Multi-Class Trajectory Prediction," Software Impacts, vol. 11, pp. 100201, Elsevier, 2021.
Bibtex 
@article{men21pytorch,
 author={Men, Qianhui and Shum, Hubert P. H.},
 journal={Software Impacts},
 title={PyTorch-Based Implementation of Label-Aware Graph Representation for Multi-Class Trajectory Prediction},
 year={2021},
 volume={11},
 pages={100201},
 numpages={3},
 doi={10.1016/j.simpa.2021.100201},
 issn={2665-9638},
 publisher={Elsevier},
}
RIS 
TY  - JOUR
AU  - Men, Qianhui
AU  - Shum, Hubert P. H.
T2  - Software Impacts
TI  - PyTorch-Based Implementation of Label-Aware Graph Representation for Multi-Class Trajectory Prediction
PY  - 2021
VL  - 11
SP  - 100201
EP  - 100201
DO  - 10.1016/j.simpa.2021.100201
SN  - 2665-9638
PB  - Elsevier
ER  - 
Paper
Data-Driven Crowd Motion Control with Multi-Touch Gestures
Data-Driven Crowd Motion Control with Multi-Touch Gestures  Invited presentation at Eurographics 2019 Impact Factor: 2.9†    Citation: 16#
Computer Graphics Forum (CGF), 2018
Yijun Shen, Joseph Henry, He Wang, Edmond S. L. Ho, Taku Komura and Hubert P. H. Shum
Webpage Cite This Plain Text 
Yijun Shen, Joseph Henry, He Wang, Edmond S. L. Ho, Taku Komura and Hubert P. H. Shum, "Data-Driven Crowd Motion Control with Multi-Touch Gestures," Computer Graphics Forum, vol. 37, no. 6, pp. 382-394, John Wiley and Sons Ltd., 2018.
Bibtex 
@article{shen18datadriven,
 author={Shen, Yijun and Henry, Joseph and Wang, He and Ho, Edmond S. L. and Komura, Taku and Shum, Hubert P. H.},
 journal={Computer Graphics Forum},
 title={Data-Driven Crowd Motion Control with Multi-Touch Gestures},
 year={2018},
 volume={37},
 number={6},
 pages={382--394},
 numpages={14},
 doi={10.1111/cgf.13333},
 issn={1467-8659},
 publisher={John Wiley and Sons Ltd.},
 Address={Chichester, UK},
}
RIS 
TY  - JOUR
AU  - Shen, Yijun
AU  - Henry, Joseph
AU  - Wang, He
AU  - Ho, Edmond S. L.
AU  - Komura, Taku
AU  - Shum, Hubert P. H.
T2  - Computer Graphics Forum
TI  - Data-Driven Crowd Motion Control with Multi-Touch Gestures
PY  - 2018
VL  - 37
IS  - 6
SP  - 382
EP  - 394
DO  - 10.1111/cgf.13333
SN  - 1467-8659
PB  - John Wiley and Sons Ltd.
ER  - 
Paper YouTube
Coordinated Crowd Simulation with Topological Scene Analysis
Coordinated Crowd Simulation with Topological Scene Analysis  Impact Factor: 2.9†    Citation: 34#
Computer Graphics Forum (CGF), 2016
Adam Barnett, Hubert P. H. Shum and Taku Komura
Webpage Cite This Plain Text 
Adam Barnett, Hubert P. H. Shum and Taku Komura, "Coordinated Crowd Simulation with Topological Scene Analysis," Computer Graphics Forum, vol. 35, no. 6, pp. 120-132, John Wiley and Sons Ltd., 2016.
Bibtex 
@article{barnett16coordinated,
 author={Barnett, Adam and Shum, Hubert P. H. and Komura, Taku},
 journal={Computer Graphics Forum},
 title={Coordinated Crowd Simulation with Topological Scene Analysis},
 year={2016},
 volume={35},
 number={6},
 pages={120--132},
 numpages={13},
 doi={10.1111/cgf.12735},
 issn={1467-8659},
 publisher={John Wiley and Sons Ltd.},
 Address={Chichester, UK},
}
RIS 
TY  - JOUR
AU  - Barnett, Adam
AU  - Shum, Hubert P. H.
AU  - Komura, Taku
T2  - Computer Graphics Forum
TI  - Coordinated Crowd Simulation with Topological Scene Analysis
PY  - 2016
VL  - 35
IS  - 6
SP  - 120
EP  - 132
DO  - 10.1111/cgf.12735
SN  - 1467-8659
PB  - John Wiley and Sons Ltd.
ER  - 
Paper YouTube
Interactive Formation Control in Complex Environments
Interactive Formation Control in Complex Environments  REF 2021 Submitted Output Impact Factor: 6.5† Top 10% Journal in Computer Science, Software Engineering†   Citation: 31#
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2014
Joseph Henry, Hubert P. H. Shum and Taku Komura
Webpage Cite This Plain Text 
Joseph Henry, Hubert P. H. Shum and Taku Komura, "Interactive Formation Control in Complex Environments," IEEE Transactions on Visualization and Computer Graphics, vol. 20, no. 2, pp. 211-222, IEEE, Feb 2014.
Bibtex 
@article{henry14interactive,
 author={Henry, Joseph and Shum, Hubert P. H. and Komura, Taku},
 journal={IEEE Transactions on Visualization and Computer Graphics},
 title={Interactive Formation Control in Complex Environments},
 year={2014},
 month={2},
 volume={20},
 number={2},
 pages={211--222},
 numpages={12},
 doi={10.1109/TVCG.2013.116},
 issn={1077-2626},
 publisher={IEEE},
}
RIS 
TY  - JOUR
AU  - Henry, Joseph
AU  - Shum, Hubert P. H.
AU  - Komura, Taku
T2  - IEEE Transactions on Visualization and Computer Graphics
TI  - Interactive Formation Control in Complex Environments
PY  - 2014
Y1  - 2 2014
VL  - 20
IS  - 2
SP  - 211
EP  - 222
DO  - 10.1109/TVCG.2013.116
SN  - 1077-2626
PB  - IEEE
ER  - 
Paper YouTube

Conference Papers

ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction
ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction    H5-Index: 232# Core A* Conference‡ 
Proceedings of the 2026 AAAI Conference on Artificial Intelligence (AAAI), 2026
Ruochen Li, Zhanxing Zhu, Tanqiu Qiao and Hubert P. H. Shum
Webpage Cite This Plain Text 
Ruochen Li, Zhanxing Zhu, Tanqiu Qiao and Hubert P. H. Shum, "ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction," in Proceedings of the 2026 AAAI Conference on Artificial Intelligence, pp. 1952, Singapore, Singapore, 2026.
Bibtex 
@inproceedings{li26vite,
 author={Li, Ruochen and Zhu, Zhanxing and Qiao, Tanqiu and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2026 AAAI Conference on Artificial Intelligence},
 title={ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction},
 year={2026},
 pages={1952},
 numpages={9},
 doi={10.1609/aaai.v40i21.38808},
 isbn={978-1-57735-906-7},
 location={Singapore, Singapore},
}
RIS 
TY  - CONF
AU  - Li, Ruochen
AU  - Zhu, Zhanxing
AU  - Qiao, Tanqiu
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2026 AAAI Conference on Artificial Intelligence
TI  - ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction
PY  - 2026
SP  - 1952
EP  - 1952
DO  - 10.1609/aaai.v40i21.38808
SN  - 978-1-57735-906-7
ER  - 
Paper Supplementary Material GitHub
Where Will They Go? Modelling Multimodal Pedestrian Manoeuvres from Ego-Centric Videos
Where Will They Go? Modelling Multimodal Pedestrian Manoeuvres from Ego-Centric Videos    H5-Index: 92# Core A Conference‡ 
Proceedings of the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026
Yuxuan Xie, Nicolas Pugeault, Chongfeng Wei, Hubert P. H. Shum and Edmond S. L. Ho
Webpage Cite This Plain Text 
Yuxuan Xie, Nicolas Pugeault, Chongfeng Wei, Hubert P. H. Shum and Edmond S. L. Ho, "Where Will They Go? Modelling Multimodal Pedestrian Manoeuvres from Ego-Centric Videos," in Proceedings of the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems, Pittsburgh, USA, IEEE/RSJ, 2026.
Bibtex 
@inproceedings{xie26where,
 author={Xie, Yuxuan and Pugeault, Nicolas and Wei, Chongfeng and Shum, Hubert P. H. and Ho, Edmond S. L.},
 booktitle={Proceedings of the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems},
 title={Where Will They Go? Modelling Multimodal Pedestrian Manoeuvres from Ego-Centric Videos},
 year={2026},
 publisher={IEEE/RSJ},
 location={Pittsburgh, USA},
}
RIS 
TY  - CONF
AU  - Xie, Yuxuan
AU  - Pugeault, Nicolas
AU  - Wei, Chongfeng
AU  - Shum, Hubert P. H.
AU  - Ho, Edmond S. L.
T2  - Proceedings of the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems
TI  - Where Will They Go? Modelling Multimodal Pedestrian Manoeuvres from Ego-Centric Videos
PY  - 2026
PB  - IEEE/RSJ
ER  - 
Paper
ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations
ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations      
Proceedings of the 2026 IEEE International Conference on Human-Machine Systems (ICHMS), 2026
Ruochen Li, Ziyi Chang, Junyan Hu, Jiannan Li, Amir Atapour-Abarghouei and Hubert P. H. Shum
Webpage Cite This Plain Text 
Ruochen Li, Ziyi Chang, Junyan Hu, Jiannan Li, Amir Atapour-Abarghouei and Hubert P. H. Shum, "ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations," in Proceedings of the 2026 IEEE International Conference on Human-Machine Systems, Singapore, Singapore, IEEE, 2026.
Bibtex 
@inproceedings{li26art,
 author={Li, Ruochen and Chang, Ziyi and Hu, Junyan and Li, Jiannan and Atapour-Abarghouei, Amir and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2026 IEEE International Conference on Human-Machine Systems},
 title={ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations},
 year={2026},
 publisher={IEEE},
 location={Singapore, Singapore},
}
RIS 
TY  - CONF
AU  - Li, Ruochen
AU  - Chang, Ziyi
AU  - Hu, Junyan
AU  - Li, Jiannan
AU  - Atapour-Abarghouei, Amir
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2026 IEEE International Conference on Human-Machine Systems
TI  - ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations
PY  - 2026
PB  - IEEE
ER  - 
Paper
Large-Scale Multi-Character Interaction Synthesis
Large-Scale Multi-Character Interaction Synthesis     Core A* Conference‡ 
Proceedings of the 2025 ACM SIGGRAPH, 2025
Ziyi Chang, He Wang, George Alex Koulieris and Hubert P. H. Shum
Webpage Cite This Plain Text 
Ziyi Chang, He Wang, George Alex Koulieris and Hubert P. H. Shum, "Large-Scale Multi-Character Interaction Synthesis," in Proceedings of the 2025 ACM SIGGRAPH, pp. Article 114, Vancouver, Canada, ACM, 2025.
Bibtex 
@inproceedings{chang25largescale,
 author={Chang, Ziyi and Wang, He and Koulieris, George Alex and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2025 ACM SIGGRAPH},
 title={Large-Scale Multi-Character Interaction Synthesis},
 year={2025},
 pages={Article 114},
 numpages={10},
 doi={10.1145/3721238.3730750},
 isbn={9.80E+12},
 publisher={ACM},
 Address={New York, NY, USA},
 location={Vancouver, Canada},
}
RIS 
TY  - CONF
AU  - Chang, Ziyi
AU  - Wang, He
AU  - Koulieris, George Alex
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2025 ACM SIGGRAPH
TI  - Large-Scale Multi-Character Interaction Synthesis
PY  - 2025
SP  - Article 114
EP  - Article 114
DO  - 10.1145/3721238.3730750
SN  - 9.80E+12
PB  - ACM
ER  - 
Paper Supplementary Material YouTube
Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery
Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery    H5-Index: 117#  Citation: 14#
Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023
Yona Falinie A. Gaus, Neelanjan Bhowmik, Brian K. S. Isaac-Medina, Hubert P. H. Shum, Amir Atapour-Abarghouei and Toby P. Breckon
Webpage Cite This Plain Text 
Yona Falinie A. Gaus, Neelanjan Bhowmik, Brian K. S. Isaac-Medina, Hubert P. H. Shum, Amir Atapour-Abarghouei and Toby P. Breckon, "Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery," in CVPRW '23: Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 2995-3005, Vancouver, Canada, IEEE/CVF, Jun 2023.
Bibtex 
@inproceedings{gaus23region,
 author={Gaus, Yona Falinie A. and Bhowmik, Neelanjan and Isaac-Medina, Brian K. S. and Shum, Hubert P. H. and Atapour-Abarghouei, Amir and Breckon, Toby P.},
 booktitle={Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
 series={CVPRW '23},
 title={Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery},
 year={2023},
 month={6},
 pages={2995--3005},
 numpages={11},
 doi={10.1109/CVPRW59228.2023.00301},
 publisher={IEEE/CVF},
 location={Vancouver, Canada},
}
RIS 
TY  - CONF
AU  - Gaus, Yona Falinie A.
AU  - Bhowmik, Neelanjan
AU  - Isaac-Medina, Brian K. S.
AU  - Shum, Hubert P. H.
AU  - Atapour-Abarghouei, Amir
AU  - Breckon, Toby P.
T2  - Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
TI  - Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery
PY  - 2023
Y1  - 6 2023
SP  - 2995
EP  - 3005
DO  - 10.1109/CVPRW59228.2023.00301
PB  - IEEE/CVF
ER  - 
Paper
Multiclass-SGCN: Sparse Graph-Based Trajectory Prediction with Agent Class Embedding
Multiclass-SGCN: Sparse Graph-Based Trajectory Prediction with Agent Class Embedding    H5-Index: 55#  Citation: 32#
Proceedings of the 2022 IEEE International Conference on Image Processing (ICIP), 2022
Ruochen Li, Stamos Katsigiannis and Hubert P. H. Shum
Webpage Cite This Plain Text 
Ruochen Li, Stamos Katsigiannis and Hubert P. H. Shum, "Multiclass-SGCN: Sparse Graph-Based Trajectory Prediction with Agent Class Embedding," in ICIP '22: Proceedings of the 2022 IEEE International Conference on Image Processing, pp. 2346-2350, Bordeaux, France, IEEE, Oct 2022.
Bibtex 
@inproceedings{li22multiclasssgcn,
 author={Li, Ruochen and Katsigiannis, Stamos and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2022 IEEE International Conference on Image Processing},
 series={ICIP '22},
 title={Multiclass-SGCN: Sparse Graph-Based Trajectory Prediction with Agent Class Embedding},
 year={2022},
 month={10},
 pages={2346--2350},
 numpages={5},
 doi={10.1109/ICIP46576.2022.9897644},
 publisher={IEEE},
 location={Bordeaux, France},
}
RIS 
TY  - CONF
AU  - Li, Ruochen
AU  - Katsigiannis, Stamos
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2022 IEEE International Conference on Image Processing
TI  - Multiclass-SGCN: Sparse Graph-Based Trajectory Prediction with Agent Class Embedding
PY  - 2022
Y1  - 10 2022
SP  - 2346
EP  - 2350
DO  - 10.1109/ICIP46576.2022.9897644
PB  - IEEE
ER  - 
Paper GitHub
Semantics-STGCNN: A Semantics-Guided Spatial-Temporal Graph Convolutional Network for Multi-Class Trajectory Prediction
Semantics-STGCNN: A Semantics-Guided Spatial-Temporal Graph Convolutional Network for Multi-Class Trajectory Prediction      Citation: 41#
Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021
Ben Rainbow, Qianhui Men and Hubert P. H. Shum
Webpage Cite This Plain Text 
Ben Rainbow, Qianhui Men and Hubert P. H. Shum, "Semantics-STGCNN: A Semantics-Guided Spatial-Temporal Graph Convolutional Network for Multi-Class Trajectory Prediction," in SMC '21: Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, pp. 2959-2966, Melbourne, Australia, IEEE, Oct 2021.
Bibtex 
@inproceedings{rainbow21semantics,
 author={Rainbow, Ben and Men, Qianhui and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics},
 series={SMC '21},
 title={Semantics-STGCNN: A Semantics-Guided Spatial-Temporal Graph Convolutional Network for Multi-Class Trajectory Prediction},
 year={2021},
 month={10},
 pages={2959--2966},
 numpages={8},
 doi={10.1109/SMC52423.2021.9658781},
 issn={2959-2966},
 publisher={IEEE},
 location={Melbourne, Australia},
}
RIS 
TY  - CONF
AU  - Rainbow, Ben
AU  - Men, Qianhui
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics
TI  - Semantics-STGCNN: A Semantics-Guided Spatial-Temporal Graph Convolutional Network for Multi-Class Trajectory Prediction
PY  - 2021
Y1  - 10 2021
SP  - 2959
EP  - 2966
DO  - 10.1109/SMC52423.2021.9658781
SN  - 2959-2966
PB  - IEEE
ER  - 
Paper YouTube
Unsupervised Abnormal Behaviour Detection with Overhead Crowd Video
Unsupervised Abnormal Behaviour Detection with Overhead Crowd Video      
Proceedings of the 2017 International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 2017
Shoujiang Xu, Edmond S. L. Ho, Nauman Aslam and Hubert P. H. Shum
Webpage Cite This Plain Text 
Shoujiang Xu, Edmond S. L. Ho, Nauman Aslam and Hubert P. H. Shum, "Unsupervised Abnormal Behaviour Detection with Overhead Crowd Video," in SKIMA '17: Proceedings of the 2017 International Conference on Software, Knowledge, Information Management and Applications, pp. 1-6, Colombo, Sri Lanka, IEEE, Dec 2017.
Bibtex 
@inproceedings{xu17unsupervised,
 author={Xu, Shoujiang and Ho, Edmond S. L. and Aslam, Nauman and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2017 International Conference on Software, Knowledge, Information Management and Applications},
 series={SKIMA '17},
 title={Unsupervised Abnormal Behaviour Detection with Overhead Crowd Video},
 year={2017},
 month={12},
 pages={1--6},
 numpages={6},
 doi={10.1109/SKIMA.2017.8294092},
 issn={2573-3214},
 publisher={IEEE},
 location={Colombo, Sri Lanka},
}
RIS 
TY  - CONF
AU  - Xu, Shoujiang
AU  - Ho, Edmond S. L.
AU  - Aslam, Nauman
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2017 International Conference on Software, Knowledge, Information Management and Applications
TI  - Unsupervised Abnormal Behaviour Detection with Overhead Crowd Video
PY  - 2017
Y1  - 12 2017
SP  - 1
EP  - 6
DO  - 10.1109/SKIMA.2017.8294092
SN  - 2573-3214
PB  - IEEE
ER  - 
Paper
Environment-Aware Real-Time Crowd Control
Environment-Aware Real-Time Crowd Control      Citation: 37#
Proceedings of the 2012 ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA), 2012
Joseph Henry, Hubert P. H. Shum and Taku Komura
Webpage Cite This Plain Text 
Joseph Henry, Hubert P. H. Shum and Taku Komura, "Environment-Aware Real-Time Crowd Control," in SCA '12: Proceedings of the 2012 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 193-200, Lausanne, Switzerland, Eurographics Association, Jul 2012.
Bibtex 
@inproceedings{henry12environment,
 author={Henry, Joseph and Shum, Hubert P. H. and Komura, Taku},
 booktitle={Proceedings of the 2012 ACM SIGGRAPH/Eurographics Symposium on Computer Animation},
 series={SCA '12},
 title={Environment-Aware Real-Time Crowd Control},
 year={2012},
 month={7},
 pages={193--200},
 numpages={8},
 isbn={978-3-905674-37-8},
 publisher={Eurographics Association},
 Address={Aire-la-Ville, Switzerland},
 location={Lausanne, Switzerland},
}
RIS 
TY  - CONF
AU  - Henry, Joseph
AU  - Shum, Hubert P. H.
AU  - Komura, Taku
T2  - Proceedings of the 2012 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
TI  - Environment-Aware Real-Time Crowd Control
PY  - 2012
Y1  - 7 2012
SP  - 193
EP  - 200
SN  - 978-3-905674-37-8
PB  - Eurographics Association
ER  - 
Paper YouTube

Eprints

VRUD: A Drone Dataset for Complex Vehicle-VRU Interactions within Mixed Traffic
VRUD: A Drone Dataset for Complex Vehicle-VRU Interactions within Mixed Traffic      
arXiv Preprint, 2026
Ziyu Wang, Hongrui Kou, Cheng Wang, Ruochen Li, Hubert P. H. Shum, Amir Atapour-Abarghouei and Yuxin Zhang
Webpage Cite This Plain Text 
Ziyu Wang, Hongrui Kou, Cheng Wang, Ruochen Li, Hubert P. H. Shum, Amir Atapour-Abarghouei and Yuxin Zhang, "VRUD: A Drone Dataset for Complex Vehicle-VRU Interactions within Mixed Traffic," arXiv preprint arXiv:2604.01134, 2026.
Bibtex 
@article{wang26vrud,
 author={Wang, Ziyu and Kou, Hongrui and Wang, Cheng and Li, Ruochen and Shum, Hubert P. H. and Atapour-Abarghouei, Amir and Zhang, Yuxin},
 journal={arXiv},
 title={VRUD: A Drone Dataset for Complex Vehicle-VRU Interactions within Mixed Traffic},
 year={2026},
 eprint={arXiv:2604.01134},
 archivePrefix={arXiv},
 primaryClass={cs.RO},
 url={https://arxiv.org/abs/2604.01134},
}
RIS 
TY  - Preprint
AU  - Wang, Ziyu
AU  - Kou, Hongrui
AU  - Wang, Cheng
AU  - Li, Ruochen
AU  - Shum, Hubert P. H.
AU  - Atapour-Abarghouei, Amir
AU  - Zhang, Yuxin
JO  - arXiv preprints
SP  - arXiv:2604.01134
KW  - cs.RO
TI  - VRUD: A Drone Dataset for Complex Vehicle-VRU Interactions within Mixed Traffic
PY  - 2026
ER  - 
Paper GitHub
Semi-Supervised Crowd Counting from Unlabeled Data
Semi-Supervised Crowd Counting from Unlabeled Data      
arXiv Preprint, 2021
Haoran Duan, Fan Wan, Rui Sun, Zeyu Wang, Varun Ojha, Yu Guan, Hubert P. H. Shum, Bingzhang Hu and Yang Long
Webpage Cite This Plain Text 
Haoran Duan, Fan Wan, Rui Sun, Zeyu Wang, Varun Ojha, Yu Guan, Hubert P. H. Shum, Bingzhang Hu and Yang Long, "Semi-Supervised Crowd Counting from Unlabeled Data," arXiv preprint arXiv:2108.13969, 2021.
Bibtex 
@article{duan21crowd,
 author={Duan, Haoran and Wan, Fan and Sun, Rui and Wang, Zeyu and Ojha, Varun and Guan, Yu and Shum, Hubert P. H. and Hu, Bingzhang and Long, Yang},
 journal={arXiv},
 title={Semi-Supervised Crowd Counting from Unlabeled Data},
 year={2021},
 numpages={24},
 eprint={arXiv:2108.13969},
 archivePrefix={arXiv},
 primaryClass={cs.CV},
 doi={10.48550/arXiv.2108.13969},
 url={https://arxiv.org/abs/2108.13969},
}
RIS 
TY  - Preprint
AU  - Duan, Haoran
AU  - Wan, Fan
AU  - Sun, Rui
AU  - Wang, Zeyu
AU  - Ojha, Varun
AU  - Guan, Yu
AU  - Shum, Hubert P. H.
AU  - Hu, Bingzhang
AU  - Long, Yang
JO  - arXiv preprints
SP  - arXiv:2108.13969
KW  - cs.CV
TI  - Semi-Supervised Crowd Counting from Unlabeled Data
PY  - 2021
DO  - 10.48550/arXiv.2108.13969
ER  - 
Paper

† According to Journal Citation Reports 2026
‡ According to ICORE Ranking 2026
# According to Google Scholar 2026


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