Research Publications - Autonomous Vehicles
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Our Autonomous Vehicles Research
We research sensing technologies using LiDAR and 360 sensors for vehicle environment modelling, spatio-temporal trajectory prediction for modelling pedestrian and vehicle behaviours, and control strategies for autonomous agents, underpinning the development of autonomous vehicles.
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Citations 100+
Interaction-Aware Decision-Making for Automated Vehicles using Social Value Orientation UKRI Trustworthy Autonomous Systems Hub AI and Robotics Research Best Paper Award Finalist Impact Factor: 14.3† Top 10% Journal in Computer Science, Artificial Intelligence† Citation: 105#
IEEE Transactions on Intelligent Vehicles (TIV), 2023
Luca Crosato, Hubert P. H. Shum, Edmond S. L. Ho and Chongfeng Wei
Topics: Robotics, Interaction Modelling, Autonomous Vehicles
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IEEE Transactions on Intelligent Vehicles (TIV), 2023
Luca Crosato, Hubert P. H. Shum, Edmond S. L. Ho and Chongfeng Wei
Topics: Robotics, Interaction Modelling, Autonomous Vehicles
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Luca Crosato, Hubert P. H. Shum, Edmond S. L. Ho and Chongfeng Wei, "Interaction-Aware Decision-Making for Automated Vehicles using Social Value Orientation," IEEE Transactions on Intelligent Vehicles, vol. 8, no. 2, pp. 1339-1349, IEEE, 2023.
Bibtex @article{crosato23interaction,
author={Crosato, Luca and Shum, Hubert P. H. and Ho, Edmond S. L. and Wei, Chongfeng},
journal={IEEE Transactions on Intelligent Vehicles},
title={Interaction-Aware Decision-Making for Automated Vehicles using Social Value Orientation},
year={2023},
volume={8},
number={2},
pages={1339--1349},
numpages={11},
doi={10.1109/TIV.2022.3189836},
issn={2379-8858},
publisher={IEEE},
}
RIS author={Crosato, Luca and Shum, Hubert P. H. and Ho, Edmond S. L. and Wei, Chongfeng},
journal={IEEE Transactions on Intelligent Vehicles},
title={Interaction-Aware Decision-Making for Automated Vehicles using Social Value Orientation},
year={2023},
volume={8},
number={2},
pages={1339--1349},
numpages={11},
doi={10.1109/TIV.2022.3189836},
issn={2379-8858},
publisher={IEEE},
}
TY - JOUR
AU - Crosato, Luca
AU - Shum, Hubert P. H.
AU - Ho, Edmond S. L.
AU - Wei, Chongfeng
T2 - IEEE Transactions on Intelligent Vehicles
TI - Interaction-Aware Decision-Making for Automated Vehicles using Social Value Orientation
PY - 2023
VL - 8
IS - 2
SP - 1339
EP - 1349
DO - 10.1109/TIV.2022.3189836
SN - 2379-8858
PB - IEEE
ER -
Paper YouTubeAU - Crosato, Luca
AU - Shum, Hubert P. H.
AU - Ho, Edmond S. L.
AU - Wei, Chongfeng
T2 - IEEE Transactions on Intelligent Vehicles
TI - Interaction-Aware Decision-Making for Automated Vehicles using Social Value Orientation
PY - 2023
VL - 8
IS - 2
SP - 1339
EP - 1349
DO - 10.1109/TIV.2022.3189836
SN - 2379-8858
PB - IEEE
ER -
Citations 50+
Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles Wiley Top Viewed Articles Impact Factor: 6.1† Top 25% Journal in Computer Science, Artificial Intelligence† Citation: 72#
Advanced Intelligent Systems (AIS), 2024
Luca Crosato, Kai Tian, Hubert P. H. Shum, Edmond S. L. Ho, Yafei Wang and Chongfeng Wei
Topics: Robotics, Literature Review, Autonomous Vehicles
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Advanced Intelligent Systems (AIS), 2024
Luca Crosato, Kai Tian, Hubert P. H. Shum, Edmond S. L. Ho, Yafei Wang and Chongfeng Wei
Topics: Robotics, Literature Review, Autonomous Vehicles
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Luca Crosato, Kai Tian, Hubert P. H. Shum, Edmond S. L. Ho, Yafei Wang and Chongfeng Wei, "Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles," Advanced Intelligent Systems, vol. 6, no. 3, pp. 2300575, Wiley, 2024.
Bibtex @article{crosato23social,
author={Crosato, Luca and Tian, Kai and Shum, Hubert P. H. and Ho, Edmond S. L. and Wang, Yafei and Wei, Chongfeng},
journal={Advanced Intelligent Systems},
title={Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles},
year={2024},
volume={6},
number={3},
pages={2300575},
numpages={23},
doi={10.1002/aisy.202300575},
issn={2640-4567},
publisher={Wiley},
}
RIS author={Crosato, Luca and Tian, Kai and Shum, Hubert P. H. and Ho, Edmond S. L. and Wang, Yafei and Wei, Chongfeng},
journal={Advanced Intelligent Systems},
title={Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles},
year={2024},
volume={6},
number={3},
pages={2300575},
numpages={23},
doi={10.1002/aisy.202300575},
issn={2640-4567},
publisher={Wiley},
}
TY - JOUR
AU - Crosato, Luca
AU - Tian, Kai
AU - Shum, Hubert P. H.
AU - Ho, Edmond S. L.
AU - Wang, Yafei
AU - Wei, Chongfeng
T2 - Advanced Intelligent Systems
TI - Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles
PY - 2024
VL - 6
IS - 3
SP - 2300575
EP - 2300575
DO - 10.1002/aisy.202300575
SN - 2640-4567
PB - Wiley
ER -
PaperAU - Crosato, Luca
AU - Tian, Kai
AU - Shum, Hubert P. H.
AU - Ho, Edmond S. L.
AU - Wang, Yafei
AU - Wei, Chongfeng
T2 - Advanced Intelligent Systems
TI - Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles
PY - 2024
VL - 6
IS - 3
SP - 2300575
EP - 2300575
DO - 10.1002/aisy.202300575
SN - 2640-4567
PB - Wiley
ER -
Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation H5-Index: 450# Core A* Conference‡ Citation: 68#
Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
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Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
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Li Li, Hubert P. H. Shum and Toby P. Breckon, "Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation," in CVPR '23: Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 9361-9371, Vancouver, Canada, IEEE/CVF, Jun 2023.
Bibtex @inproceedings{li23less,
author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
series={CVPR '23},
title={Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation},
year={2023},
month={6},
pages={9361--9371},
numpages={11},
doi={10.1109/CVPR52729.2023.00903},
publisher={IEEE/CVF},
location={Vancouver, Canada},
}
RIS author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
series={CVPR '23},
title={Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation},
year={2023},
month={6},
pages={9361--9371},
numpages={11},
doi={10.1109/CVPR52729.2023.00903},
publisher={IEEE/CVF},
location={Vancouver, Canada},
}
TY - CONF
AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition
TI - Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation
PY - 2023
Y1 - 6 2023
SP - 9361
EP - 9371
DO - 10.1109/CVPR52729.2023.00903
PB - IEEE/CVF
ER -
Paper Supplementary Material GitHub YouTubeAU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition
TI - Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation
PY - 2023
Y1 - 6 2023
SP - 9361
EP - 9371
DO - 10.1109/CVPR52729.2023.00903
PB - IEEE/CVF
ER -
Citations 30+
Semantics-STGCNN: A Semantics-Guided Spatial-Temporal Graph Convolutional Network for Multi-Class Trajectory Prediction Citation: 37#
Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021
Ben Rainbow, Qianhui Men and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021
Ben Rainbow, Qianhui Men and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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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 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},
}
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 YouTubeAU - 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 -
DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications H5-Index: 56# Citation: 33#
Proceedings of the 2021 International Conference on 3D Vision (3DV), 2021
Li Li, Khalid N. Ismail, Hubert P. H. Shum and Toby P. Breckon
Topics: Robotics, 3D Reconstruction, Environment Sensing, Datasets, Autonomous Vehicles
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Proceedings of the 2021 International Conference on 3D Vision (3DV), 2021
Li Li, Khalid N. Ismail, Hubert P. H. Shum and Toby P. Breckon
Topics: Robotics, 3D Reconstruction, Environment Sensing, Datasets, Autonomous Vehicles
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Li Li, Khalid N. Ismail, Hubert P. H. Shum and Toby P. Breckon, "DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications," in 3DV '21: Proceedings of the 2021 International Conference on 3D Vision, pp. 1227-1237, IEEE, Dec 2021.
Bibtex @inproceedings{li21durlar,
author={Li, Li and Ismail, Khalid N. and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2021 International Conference on 3D Vision},
series={3DV '21},
title={DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications},
year={2021},
month={12},
pages={1227--1237},
numpages={11},
doi={10.1109/3DV53792.2021.00130},
publisher={IEEE},
}
RIS author={Li, Li and Ismail, Khalid N. and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2021 International Conference on 3D Vision},
series={3DV '21},
title={DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications},
year={2021},
month={12},
pages={1227--1237},
numpages={11},
doi={10.1109/3DV53792.2021.00130},
publisher={IEEE},
}
TY - CONF
AU - Li, Li
AU - Ismail, Khalid N.
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2021 International Conference on 3D Vision
TI - DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications
PY - 2021
Y1 - 12 2021
SP - 1227
EP - 1237
DO - 10.1109/3DV53792.2021.00130
PB - IEEE
ER -
Paper Dataset GitHub YouTubeAU - Li, Li
AU - Ismail, Khalid N.
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2021 International Conference on 3D Vision
TI - DurLAR: A High-fidelity 128-Channel LiDAR Dataset with Panoramic Ambientand Reflectivity Imagery for Multi-Modal Autonomous Driving Applications
PY - 2021
Y1 - 12 2021
SP - 1227
EP - 1237
DO - 10.1109/3DV53792.2021.00130
PB - IEEE
ER -
Citations 20+
Human-Centric Autonomous Driving in an AV-Pedestrian Interactive Environment Using SVO Best Paper Award Citation: 29#
Proceedings of the 2021 IEEE International Conference on Human-Machine Systems (ICHMS), 2021
Luca Crosato, Chongfeng Wei, Edmond S. L. Ho and Hubert P. H. Shum
Topics: Robotics, Interaction Modelling, Autonomous Vehicles
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Proceedings of the 2021 IEEE International Conference on Human-Machine Systems (ICHMS), 2021
Luca Crosato, Chongfeng Wei, Edmond S. L. Ho and Hubert P. H. Shum
Topics: Robotics, Interaction Modelling, Autonomous Vehicles
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Luca Crosato, Chongfeng Wei, Edmond S. L. Ho and Hubert P. H. Shum, "Human-Centric Autonomous Driving in an AV-Pedestrian Interactive Environment Using SVO," in ICHMS '21: Proceedings of the 2021 IEEE International Conference on Human-Machine Systems, pp. 1-6, Magdeburg, Germany, IEEE, Sep 2021.
Bibtex @inproceedings{luca21humancentric,
author={Crosato, Luca and Wei, Chongfeng and Ho, Edmond S. L. and Shum, Hubert P. H.},
booktitle={Proceedings of the 2021 IEEE International Conference on Human-Machine Systems},
series={ICHMS '21},
title={Human-Centric Autonomous Driving in an AV-Pedestrian Interactive Environment Using SVO},
year={2021},
month={9},
pages={1--6},
numpages={6},
doi={10.1109/ICHMS53169.2021.9582640},
publisher={IEEE},
location={Magdeburg, Germany},
}
RIS author={Crosato, Luca and Wei, Chongfeng and Ho, Edmond S. L. and Shum, Hubert P. H.},
booktitle={Proceedings of the 2021 IEEE International Conference on Human-Machine Systems},
series={ICHMS '21},
title={Human-Centric Autonomous Driving in an AV-Pedestrian Interactive Environment Using SVO},
year={2021},
month={9},
pages={1--6},
numpages={6},
doi={10.1109/ICHMS53169.2021.9582640},
publisher={IEEE},
location={Magdeburg, Germany},
}
TY - CONF
AU - Crosato, Luca
AU - Wei, Chongfeng
AU - Ho, Edmond S. L.
AU - Shum, Hubert P. H.
T2 - Proceedings of the 2021 IEEE International Conference on Human-Machine Systems
TI - Human-Centric Autonomous Driving in an AV-Pedestrian Interactive Environment Using SVO
PY - 2021
Y1 - 9 2021
SP - 1
EP - 6
DO - 10.1109/ICHMS53169.2021.9582640
PB - IEEE
ER -
Paper YouTubeAU - Crosato, Luca
AU - Wei, Chongfeng
AU - Ho, Edmond S. L.
AU - Shum, Hubert P. H.
T2 - Proceedings of the 2021 IEEE International Conference on Human-Machine Systems
TI - Human-Centric Autonomous Driving in an AV-Pedestrian Interactive Environment Using SVO
PY - 2021
Y1 - 9 2021
SP - 1
EP - 6
DO - 10.1109/ICHMS53169.2021.9582640
PB - IEEE
ER -
Multiclass-SGCN: Sparse Graph-Based Trajectory Prediction with Agent Class Embedding H5-Index: 55# Citation: 28#
Proceedings of the 2022 IEEE International Conference on Image Processing (ICIP), 2022
Ruochen Li, Stamos Katsigiannis and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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Proceedings of the 2022 IEEE International Conference on Image Processing (ICIP), 2022
Ruochen Li, Stamos Katsigiannis and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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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 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},
}
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 GitHubAU - 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 -
RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation Oral Paper (Top 2.3% of 8585 Submissions) H5-Index: 262# Core A* Conference‡ Citation: 25#
Proceedings of the 2024 European Conference on Computer Vision (ECCV), 2024
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
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Proceedings of the 2024 European Conference on Computer Vision (ECCV), 2024
Li Li, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
Webpage Cite This Plain Text
Li Li, Hubert P. H. Shum and Toby P. Breckon, "RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation," in ECCV '24: Proceedings of the 2024 European Conference on Computer Vision, vol. 15065, pp. 222-241, Milan, Italy, Springer, 2024.
Bibtex @inproceedings{li24rapidseg,
author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 European Conference on Computer Vision},
series={ECCV '24},
title={RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation},
year={2024},
volume={15065},
pages={222--241},
numpages={20},
doi={10.1007/978-3-031-72667-5_13},
publisher={Springer},
location={Milan, Italy},
}
RIS author={Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 European Conference on Computer Vision},
series={ECCV '24},
title={RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation},
year={2024},
volume={15065},
pages={222--241},
numpages={20},
doi={10.1007/978-3-031-72667-5_13},
publisher={Springer},
location={Milan, Italy},
}
TY - CONF
AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 European Conference on Computer Vision
TI - RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation
PY - 2024
VL - 15065
SP - 222
EP - 241
DO - 10.1007/978-3-031-72667-5_13
PB - Springer
ER -
Paper Supplementary Material GitHub YouTube Part 1 YouTube Part 2AU - Li, Li
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 European Conference on Computer Vision
TI - RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation
PY - 2024
VL - 15065
SP - 222
EP - 241
DO - 10.1007/978-3-031-72667-5_13
PB - Springer
ER -
Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction Impact Factor: 11.1† Top 10% Journal in Engineering, Electrical & Electronic† Citation: 20#
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2025
Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis, Zhanxing Zhu and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2025
Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis, Zhanxing Zhu and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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 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},
}
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 GitHubAU - 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 -
Citations 10+
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: 15#
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025
Ruochen Li, Stamos Katsigiannis, Tae-Kyun Kim and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
Webpage Cite This Plain Text
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025
Ruochen Li, Stamos Katsigiannis, Tae-Kyun Kim and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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 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},
}
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 MaterialAU - 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 -
Formation Control for UAVs Using a Flux Guided Approach Impact Factor: 7.5† Top 25% Journal in Computer Science, Artificial Intelligence† Citation: 14#
Expert Systems with Applications (ESWA), 2022
John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang and Subramanian Ramamoorthy
Topics: Crowd Modelling, Robotics, Air and Space, Autonomous Vehicles
Webpage Cite This Plain Text
Expert Systems with Applications (ESWA), 2022
John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang and Subramanian Ramamoorthy
Topics: Crowd Modelling, Robotics, Air and Space, Autonomous Vehicles
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 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},
}
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 YouTubeAU - 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 -
A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection H5-Index: 52# Core A* Conference‡ Citation: 13#
Proceedings of the 2024 ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024
Luca Crosato, Chongfeng Wei, Edmond S. L. Ho, Hubert P. H. Shum and Yuzhu Sun
Topics: Robotics, Interaction Modelling, Autonomous Vehicles
Webpage Cite This Plain Text
Proceedings of the 2024 ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024
Luca Crosato, Chongfeng Wei, Edmond S. L. Ho, Hubert P. H. Shum and Yuzhu Sun
Topics: Robotics, Interaction Modelling, Autonomous Vehicles
Webpage Cite This Plain Text
Luca Crosato, Chongfeng Wei, Edmond S. L. Ho, Hubert P. H. Shum and Yuzhu Sun, "A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection," in HRI '24: Proceedings of the 2024 ACM/IEEE International Conference on Human Robot Interaction, pp. 167-174, Colorado, USA, ACM/IEEE, 2024.
Bibtex @inproceedings{crosato24virtual,
author={Crosato, Luca and Wei, Chongfeng and Ho, Edmond S. L. and Shum, Hubert P. H. and Sun, Yuzhu},
booktitle={Proceedings of the 2024 ACM/IEEE International Conference on Human Robot Interaction},
series={HRI '24},
title={A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection},
year={2024},
pages={167--174},
numpages={8},
doi={10.1145/3610977.3634923},
isbn={9.80E+12},
publisher={ACM/IEEE},
location={Colorado, USA},
}
RIS author={Crosato, Luca and Wei, Chongfeng and Ho, Edmond S. L. and Shum, Hubert P. H. and Sun, Yuzhu},
booktitle={Proceedings of the 2024 ACM/IEEE International Conference on Human Robot Interaction},
series={HRI '24},
title={A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection},
year={2024},
pages={167--174},
numpages={8},
doi={10.1145/3610977.3634923},
isbn={9.80E+12},
publisher={ACM/IEEE},
location={Colorado, USA},
}
TY - CONF
AU - Crosato, Luca
AU - Wei, Chongfeng
AU - Ho, Edmond S. L.
AU - Shum, Hubert P. H.
AU - Sun, Yuzhu
T2 - Proceedings of the 2024 ACM/IEEE International Conference on Human Robot Interaction
TI - A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection
PY - 2024
SP - 167
EP - 174
DO - 10.1145/3610977.3634923
SN - 9.80E+12
PB - ACM/IEEE
ER -
PaperAU - Crosato, Luca
AU - Wei, Chongfeng
AU - Ho, Edmond S. L.
AU - Shum, Hubert P. H.
AU - Sun, Yuzhu
T2 - Proceedings of the 2024 ACM/IEEE International Conference on Human Robot Interaction
TI - A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection
PY - 2024
SP - 167
EP - 174
DO - 10.1145/3610977.3634923
SN - 9.80E+12
PB - ACM/IEEE
ER -
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
Topics: Crowd Modelling, Autonomous Vehicles
Webpage Cite This Plain Text
Software Impacts (SIMPAC), 2021
Qianhui Men and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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 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},
}
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 -
PaperAU - 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 -
Citations 0+
Multi-Task Deep Learning with Optical Flow Features for Self-Driving Cars Impact Factor: 2.5†
IET Intelligent Transport Systems (ITS), 2020
Yuan Hu, Hubert P. H. Shum and Edmond S. L. Ho
Topics: Robotics, Video Analysis, Autonomous Vehicles
Webpage Cite This Plain Text
IET Intelligent Transport Systems (ITS), 2020
Yuan Hu, Hubert P. H. Shum and Edmond S. L. Ho
Topics: Robotics, Video Analysis, Autonomous Vehicles
Webpage Cite This Plain Text
Yuan Hu, Hubert P. H. Shum and Edmond S. L. Ho, "Multi-Task Deep Learning with Optical Flow Features for Self-Driving Cars," IET Intelligent Transport Systems, vol. 14, no. 13, pp. 1845-1854, Institution of Engineering and Technology, 2020.
Bibtex @article{hu21multitask,
author={Hu, Yuan and Shum, Hubert P. H. and Ho, Edmond S. L.},
journal={IET Intelligent Transport Systems},
title={Multi-Task Deep Learning with Optical Flow Features for Self-Driving Cars},
year={2020},
volume={14},
number={13},
pages={1845--1854},
numpages={10},
doi={10.1049/iet-its.2020.0439},
issn={1751-956X},
publisher={Institution of Engineering and Technology},
}
RIS author={Hu, Yuan and Shum, Hubert P. H. and Ho, Edmond S. L.},
journal={IET Intelligent Transport Systems},
title={Multi-Task Deep Learning with Optical Flow Features for Self-Driving Cars},
year={2020},
volume={14},
number={13},
pages={1845--1854},
numpages={10},
doi={10.1049/iet-its.2020.0439},
issn={1751-956X},
publisher={Institution of Engineering and Technology},
}
TY - JOUR
AU - Hu, Yuan
AU - Shum, Hubert P. H.
AU - Ho, Edmond S. L.
T2 - IET Intelligent Transport Systems
TI - Multi-Task Deep Learning with Optical Flow Features for Self-Driving Cars
PY - 2020
VL - 14
IS - 13
SP - 1845
EP - 1854
DO - 10.1049/iet-its.2020.0439
SN - 1751-956X
PB - Institution of Engineering and Technology
ER -
PaperAU - Hu, Yuan
AU - Shum, Hubert P. H.
AU - Ho, Edmond S. L.
T2 - IET Intelligent Transport Systems
TI - Multi-Task Deep Learning with Optical Flow Features for Self-Driving Cars
PY - 2020
VL - 14
IS - 13
SP - 1845
EP - 1854
DO - 10.1049/iet-its.2020.0439
SN - 1751-956X
PB - Institution of Engineering and Technology
ER -
TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training H5-Index: 57# Core A Conference‡
Proceedings of the 2024 British Machine Vision Conference (BMVC), 2024
Li Li, Tanqiu Qiao, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
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Proceedings of the 2024 British Machine Vision Conference (BMVC), 2024
Li Li, Tanqiu Qiao, Hubert P. H. Shum and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
Webpage Cite This Plain Text
Li Li, Tanqiu Qiao, Hubert P. H. Shum and Toby P. Breckon, "TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training," in BMVC '24: Proceedings of the 2024 British Machine Vision Conference, Glasgow, UK, 2024.
Bibtex @inproceedings{li24traildet,
author={Li, Li and Qiao, Tanqiu and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 British Machine Vision Conference},
series={BMVC '24},
title={TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training},
year={2024},
location={Glasgow, UK},
}
RIS author={Li, Li and Qiao, Tanqiu and Shum, Hubert P. H. and Breckon, Toby P.},
booktitle={Proceedings of the 2024 British Machine Vision Conference},
series={BMVC '24},
title={TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training},
year={2024},
location={Glasgow, UK},
}
TY - CONF
AU - Li, Li
AU - Qiao, Tanqiu
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 British Machine Vision Conference
TI - TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training
PY - 2024
ER -
Paper Supplementary MaterialAU - Li, Li
AU - Qiao, Tanqiu
AU - Shum, Hubert P. H.
AU - Breckon, Toby P.
T2 - Proceedings of the 2024 British Machine Vision Conference
TI - TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training
PY - 2024
ER -
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
Topics: Crowd Modelling, Autonomous Vehicles
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Proceedings of the 2026 AAAI Conference on Artificial Intelligence (AAAI), 2026
Ruochen Li, Zhanxing Zhu, Tanqiu Qiao and Hubert P. H. Shum
Topics: Crowd Modelling, Autonomous Vehicles
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, 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},
location={Singapore, Singapore},
}
RIS 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},
location={Singapore, Singapore},
}
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
ER -
Paper Supplementary MaterialAU - 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
ER -
KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation H5-Index: 131# Core A Conference‡
Proceedings of the 2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2026
Wenke E, Yixin Sun, Jiaxu Liu, Hubert P. H. Shum, Amir Atapour-Abarghouei and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
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Proceedings of the 2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2026
Wenke E, Yixin Sun, Jiaxu Liu, Hubert P. H. Shum, Amir Atapour-Abarghouei and Toby P. Breckon
Topics: Environment Sensing, Autonomous Vehicles
Webpage Cite This Plain Text
Wenke E, Yixin Sun, Jiaxu Liu, Hubert P. H. Shum, Amir Atapour-Abarghouei and Toby P. Breckon, "KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation," in Proceedings of the 2026 IEEE/CVF Winter Conference on Applications of Computer Vision, Arizona, USA, IEEE/CVF, 2026.
Bibtex @inproceedings{e26kd360,
author={E, Wenke and Sun, Yixin and Liu, Jiaxu and Shum, Hubert P. H. and Atapour-Abarghouei, Amir and Breckon, Toby P.},
booktitle={Proceedings of the 2026 IEEE/CVF Winter Conference on Applications of Computer Vision},
title={KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation},
year={2026},
publisher={IEEE/CVF},
location={Arizona, USA},
}
RIS author={E, Wenke and Sun, Yixin and Liu, Jiaxu and Shum, Hubert P. H. and Atapour-Abarghouei, Amir and Breckon, Toby P.},
booktitle={Proceedings of the 2026 IEEE/CVF Winter Conference on Applications of Computer Vision},
title={KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation},
year={2026},
publisher={IEEE/CVF},
location={Arizona, USA},
}
TY - CONF
AU - E, Wenke
AU - Sun, Yixin
AU - Liu, Jiaxu
AU - Shum, Hubert P. H.
AU - Atapour-Abarghouei, Amir
AU - Breckon, Toby P.
T2 - Proceedings of the 2026 IEEE/CVF Winter Conference on Applications of Computer Vision
TI - KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation
PY - 2026
PB - IEEE/CVF
ER -
Paper Supplementary Material YouTubeAU - E, Wenke
AU - Sun, Yixin
AU - Liu, Jiaxu
AU - Shum, Hubert P. H.
AU - Atapour-Abarghouei, Amir
AU - Breckon, Toby P.
T2 - Proceedings of the 2026 IEEE/CVF Winter Conference on Applications of Computer Vision
TI - KD360-VoxelBEV: LiDAR and 360-Degree Camera Cross Modality Knowledge Distillation for Bird’s-Eye-View Segmentation
PY - 2026
PB - IEEE/CVF
ER -
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
Topics: Crowd Modelling, Autonomous Vehicles
Webpage Cite This Plain Text
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
Topics: Crowd Modelling, Autonomous Vehicles
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, 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},
location={Singapore, Singapore},
}
RIS 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},
location={Singapore, Singapore},
}
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
ER -
PaperAU - 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
ER -
Benchmarking Autonomous Vehicles: A Driver Foundation Model Framework
Proceeding of the 2026 International Workshop on Critical Automotive Applications: Robustness & Safety (CARS), 2026
Yuxin Zhang, Cheng Wang and Hubert P. H. Shum
Topics: Robotics, Autonomous Vehicles
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Proceeding of the 2026 International Workshop on Critical Automotive Applications: Robustness & Safety (CARS), 2026
Yuxin Zhang, Cheng Wang and Hubert P. H. Shum
Topics: Robotics, Autonomous Vehicles
Webpage Cite This Plain Text
Yuxin Zhang, Cheng Wang and Hubert P. H. Shum, "Benchmarking Autonomous Vehicles: A Driver Foundation Model Framework," in Proceeding of the 2026 International Workshop on Critical Automotive Applications: Robustness & Safety, Munich, Germany, 2026.
Bibtex @article{zhang26benchmarking,
author={Zhang, Yuxin and Wang, Cheng and Shum, Hubert P. H.},
booktitle={Proceeding of the 2026 International Workshop on Critical Automotive Applications: Robustness & Safety},
title={Benchmarking Autonomous Vehicles: A Driver Foundation Model Framework},
year={2026},
numpages={4},
location={Munich, Germany},
}
RIS author={Zhang, Yuxin and Wang, Cheng and Shum, Hubert P. H.},
booktitle={Proceeding of the 2026 International Workshop on Critical Automotive Applications: Robustness & Safety},
title={Benchmarking Autonomous Vehicles: A Driver Foundation Model Framework},
year={2026},
numpages={4},
location={Munich, Germany},
}
TY - JOUR
AU - Zhang, Yuxin
AU - Wang, Cheng
AU - Shum, Hubert P. H.
T2 - Proceeding of the 2026 International Workshop on Critical Automotive Applications: Robustness & Safety
TI - Benchmarking Autonomous Vehicles: A Driver Foundation Model Framework
PY - 2026
ER -
PaperAU - Zhang, Yuxin
AU - Wang, Cheng
AU - Shum, Hubert P. H.
T2 - Proceeding of the 2026 International Workshop on Critical Automotive Applications: Robustness & Safety
TI - Benchmarking Autonomous Vehicles: A Driver Foundation Model Framework
PY - 2026
ER -
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
Topics: Robotics, Crowd Modelling, Datasets, Autonomous Vehicles
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arXiv Preprint, 2026
Ziyu Wang, Hongrui Kou, Cheng Wang, Ruochen Li, Hubert P. H. Shum, Amir Atapour-Abarghouei and Yuxin Zhang
Topics: Robotics, Crowd Modelling, Datasets, Autonomous Vehicles
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 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},
}
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 -
GitHubAU - 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 -