Staff profile

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Research Interests: Computer Vision, Computer Graphics, Machine Learning, Biomedical Engineering

Dr Hubert P. H. Shum is an Associate Professor and the Deputy Director of Research in the Department of Computer Science at Durham University researching on spatio-temporal visual computing. His research is fundamental to many disciplines, facilitating him to engage in various multidisciplinary research centres. He is a Co-Founder of the Responsible Space Innovation Centre, a Fellow of the Wolfson Research Institute for Health and Wellbeing, and a Steering Group Member of the Centre for Visual Arts and Culture. Before this, he worked as the Director of Research/Associate Professor/Senior Lecturer at Northumbria University, and a Postdoctoral Researcher at RIKEN Japan. He received his PhD degree from the University of Edinburgh, and his Master's and Bachelor's degrees from the City University of Hong Kong.

To develop his team, he has led research projects as the Principal Investigator awarded by EPSRC, the Ministry of Defence, the Royal Society and Innovate UK. He has also been a Co-Investigator in NortHFutures, a £4.17 mil EPSRC project to found a new digital health hub in the North East England. These have facilitated him to have supervised more than 30 PhDs, recruited multiple Post-doctoral Researchers, and collaborated with international researchers from the UK, China, France, Japan and India. To engage the academic and industrial networks, he has chaired international conferences such as Pacific Graphics, BMVC, ACM SIGGRAPH/Eurographics SCA and ACM SIGGRAPH MIG. Contributing to the research community, he has served as an Associate Editor for Computer Graphics Forum, a Guest Editor for the International Journal of Computer Vision, and a Program Committee member in 19 conferences such as Eurographics, CVPR and Pacific Graphics.

He has authored over 150 research publications in the fields of computer vision, computer graphics, machine learning and biomedical engineering, particularly focusing on modelling human-related data with deep learning.

Joining Us

If you aspire to develop yourself and conduct high-quality research, do explore working with the team as a PhD student, a visiting/internship student, or an academic visitor. Dr Shum's team has a supportive culture with members developing successful research and enjoying their vibrant lifes in the UK. See further information and application procedures.

Some self-funded PhD oppotunities include:

• Biomedical Engineering with Deep Learning based Video Analysis
• Computer Vision with Deep Learning for Human Data Modelling
• Deep Learning based Computer Graphics for Creating Virtual Characters

Recent Research

Research Grants

• EPSRC Digital Health Hub Pilot Scheme (Ref: EP/X031012/1), "Northern Health Futures Hub (NortHFutures)", Co-investigator, £4.17 million
• Knowledge Transfer Partnership (Ref: 10050391), "Skin Lesion Classification with Real-World Data", Principal Investigator, £143,393
• Durham University Strategy Research Fund, "Durham University Responsible Space Innovation Centre", Co-Founder and Co-Investigator, Department of Computer Science Leader, £2.5 million
• Defence and Security Accelerator (Ref: DSTL0000007030, ACC6031106), "Autonomous Persistent Wide Area Surveillance of Human and Vehicle Activity", Co-investigator, £93,978
• Security Technology Research Innovation Grants Programme (Ref: 007CD), "Tracking Drones Across Different Platforms with Machine Vision", Principal Investigator
• Defence and Security Accelerator (Ref: DSTLX-1000140725), "D-FOCUS: Drone-FOrmation Control for countering future Unmanned aerial Systems", Principal Investigator, £124,901
• GX Project Grants Scheme, "Wound Monitoring with Depth Cameras on Portable Systems", Principal Investigator
• Royal Society International Exchanges (Ref: IES\R2\181024), "Modelling Human Motion for Synthesis and Recognition with Deep Learning on Surface Features", Principal Investigator
• Royal Society International Exchanges (Ref: IE160609), "An Affective Smart Environment for Personalized Learning and Teaching", Principal Investigator
• Erasmus Mundus Action 2 Programme (Ref: 2014-0861/001-001), "Sustainable Green Economies through Learning, Innovation, Networking and Knowledge Exchange (gLink)", Northumbria University Funding Management Officer, €3.03 million
• EPSRC (Ref: EP/M002632/1), "Interaction-based Human Motion Analysis", Principal Investigator, £123,819

• 2000: Deputy Director of Research:
• 2000: Steering Committee Member of the Centre for Visual Arts and Culture:

Conference Paper

• Lu, Z., Wang, H., Chang, Z., Yang, G., & Shum, H. P. (in press). Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient.
• Zhou, K., Chen, C., Ma, Y., Leng, Z., Shum, H. P., Li, F. W., & Liang, X. (in press). A Mixed Reality Training System for Hand-Object Interaction in Simulated Microgravity Environments. In Proceedings of the 2023 International Symposium on Mixed and Augmented Reality
• Liu, J., Yu, Z., Breckon, T. P., & Shum, H. P. H. (in press). U3DS3 : Unsupervised 3D Semantic Scene Segmentation.
• Feng, Q., Shum, H. P., & Morishima, S. (in press). Enhancing Perception and Immersion in Pre-Captured Environments through Learning-Based Eye Height Adaptation. In Proceedings of the 2023 International Symposium on Mixed and Augmented Reality
• Zhang, X., Zheng, S., Shum, H. P., Zhang, H., Song, N., Song, M., & Jia, H. (in press). Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRI.
• Corona-Figueroa, A., Bond-Taylor, S., Bhowmik, N., Gaus, Y. F. A., Breckon, T. P., Shum, H. P., & Willcocks, C. G. (in press). Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers. In ICCV '23: Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision
• Chang, Z., Findlay, E. J., Zhang, H., & Shum, H. P. (2023). Unifying Human Motion Synthesis and Style Transfer with Denoising Diffusion Probabilistic Models. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - GRAPP (64-74). https://doi.org/10.5220/0011631000003417
• Gaus, Y., Bhowmik, N., Issac-Medina, B., Atapour-Abarghouei, A., Shum, H., & Breckon, T. (2023). Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). https://doi.org/10.1109/CVPRW59228.2023.00301
• Vijendran, M., Li, F. W., & Shum, H. P. (2023). Tackling Data Bias in Painting Classification with Style Transfer. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 VISAPP: VISAPP (250-261). https://doi.org/10.5220/0011776600003417
• Li, L., Shum, H. P., & Breckon, T. P. (2023). Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/CVPR52729.2023.00903
• Chang, Z., Koulieris, G. A., & Shum, H. P. (2022). 3D Reconstruction of Sculptures from Single Images via Unsupervised Domain Adaptation on Implicit Models. . https://doi.org/10.1145/3562939.3565632
• Li, R., Katsigiannis, S., & Shum, H. P. (2022). Multiclass-SGCN: Sparse Graph-based Trajectory Prediction with Agent Class Embedding. In 2022 IEEE International Conference on Image Processing (ICIP) Proceedings (2346-2350). https://doi.org/10.1109/icip46576.2022.9897644
• Corona-Figueroa, A., Frawley, J., Bond-Taylor, S., Bethapudi, S., Shum, H. P., & Willcocks, C. G. (2022). MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray. . https://doi.org/10.1109/embc48229.2022.9871757
• Qiao, T., Men, Q., Li, F. W., Kubotani, Y., Morishima, S., & Shum, H. P. (2022). Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos. . https://doi.org/10.1007/978-3-031-19772-7_28
• Chen, S., Atapour-Abarghouei, A., Kerby, J., Ho, E. S., Sainsbury, D. C., Butterworth, S., & Shum, H. P. (2022). A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip. . https://doi.org/10.1109/bhi56158.2022.9926917
• Zhang, X., Zhang, H., & Shum, H. P. (2022). Pose-based Tremor Classification for Parkinson’s Disease Diagnosis from Video. . https://doi.org/10.1007/978-3-031-16440-8_47
• Organisciak, D., Poyser, M., Alsehaim, A., Hu, S., Isaac-Medina, B. K., Breckon, T. P., & Shum, H. P. (2022). UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery. . https://doi.org/10.5220/0010836600003124
• Zhang, X., Al Moubayed, N., & Shum, H. P. (2022). Towards Graph Representation Learning Based Surgical Workflow Anticipation. . https://doi.org/10.1109/bhi56158.2022.9926801
• Feng, Q., Shum, H. P., & Morishima, S. (2022). 360 Depth Estimation in the Wild - The Depth360 Dataset and the SegFuse Network. . https://doi.org/10.1109/vr51125.2022.00087
• Li, L., Ismail, K. N., Shum, H. P., & Breckon, T. P. (2021). DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications. . https://doi.org/10.1109/3dv53792.2021.00130
• Zhou, K., Cheng, Z., Shum, H. P., Li, F. W., & Liang, X. (2021). STGAE: Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising. . https://doi.org/10.1109/ismar52148.2021.00018
• Isaac-Medina, B. K., Poyser, M., Organisciak, D., Willcocks, C. G., Breckon, T. P., & Shum, H. P. (2021). Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark. . https://doi.org/10.1109/iccvw54120.2021.00142
• Leng, Z., Chen, J., Shum, H. P., Li, F. W., & Liang, X. (2021). Stable Hand Pose Estimation under Tremor via Graph Neural Network. In 2021 IEEE Virtual Reality and 3D User Interfaces (VR) (226-234). https://doi.org/10.1109/vr50410.2021.00044

Journal Article

• Zhou, K., Shum, H. P., Li, F. W., & Liang, X. (in press). Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising. IEEE Transactions on Visualization and Computer Graphics,
• Crosato, L., Tian, K., Shum, H. P., Ho, E. S., Wang, Y., & Wei, C. (in press). Social Interaction-Aware Dynamical Models and Decision Making for Autonomous Vehicles. Advanced Intelligent Systems,
• Zhou, K., Ma, Y., Shum, H. P., & Liang, X. (2023). Hierarchical Graph Convolutional Networks for Action Quality Assessment. IEEE Transactions on Circuits and Systems for Video Technology, https://doi.org/10.1109/TCSVT.2023.3281413
• Chen, S., Atapour-Abarghouei, A., Ho, E. S., & Shum, H. P. (2023). INCLG: Inpainting for Non-Cleft Lip Generation with a Multi-Task Image Processing Network. Software impacts, 17, Article 100517. https://doi.org/10.1016/j.simpa.2023.100517
• Zhou, K., Cai, R., Ma, Y., Tan, Q., Wang, X., Li, J., …Liang, X. (2023). A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis. IEEE Transactions on Visualization and Computer Graphics, 29(5), 2456-2466. https://doi.org/10.1109/tvcg.2023.3247092
• Crosato, L., Shum, H. P., Ho, E. S., & Wei, C. (2023). Interaction-aware Decision-making for Automated Vehicles using Social Value Orientation. IEEE Transactions on Intelligent Vehicles, 8(2), 1339-1349. https://doi.org/10.1109/tiv.2022.3189836
• McCay, K. D., Hu, P., Shum, H. P., Woo, W. L., Marcroft, C., Embleton, N. D., …Ho, E. S. (2022). A Pose-based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 8-19. https://doi.org/10.1109/tnsre.2021.3138185
• Men, Q., Ho, E. S., Shum, H. P., & Leung, H. (2021). A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction. IEEE Transactions on Circuits and Systems for Video Technology, 31(9), 3417-3432. https://doi.org/10.1109/tcsvt.2020.3038145
• Hu, S., Shum, H. P., Liang, X., Li, F. W., & Aslam, N. (2021). Facial reshaping operator for controllable face beautification. Expert Systems with Applications, 167, Article 114067. https://doi.org/10.1016/j.eswa.2020.114067
• Hu, S., Shum, H., Aslam, N., Li, F. W., & Liang, X. (2020). A Unified Deep Metric Representation for Mesh Saliency Detection and Non-rigid Shape Matching. IEEE Transactions on Multimedia, 22(9), 2278-2292. https://doi.org/10.1109/tmm.2019.2952983
• Zhang, Z., Ma, Y., Li, Y., Li, F. W., Shum, H. P., Yang, B., …Liang, X. (2020). Cumuliform Cloud Formation Control using Parameter-Predicting Convolutional Neural Network. Graphical Models, 111, Article 101083. https://doi.org/10.1016/j.gmod.2020.101083
• Hu, S., Liang, X., Shum, H. P., Li, F. W., & Aslam, N. (2020). Sparse Metric-based Mesh Saliency. Neurocomputing, 400, 11-23. https://doi.org/10.1016/j.neucom.2020.02.106
• Shen, Y., Yang, L., Ho, E. S., & Shum, H. P. (2020). Interaction-Based Human Activity Comparison. IEEE Transactions on Visualization and Computer Graphics, 26(8), 2620-2633. https://doi.org/10.1109/tvcg.2019.2893247
• Kar, A., Pramanik, S., Chakraborty, A., Bhattacharjee, D., Ho, E. S., & Shum, H. P. (2020). LMZMPM: Local Modified Zernike Moment Per-unit Mass for Robust Human Face Recognition. IEEE Transactions on Information Forensics and Security, 16, 495-509. https://doi.org/10.1109/tifs.2020.3015552
• Bhattacharya, M., Roy, S., Mistry, K., Shum, H. P., & Chattopadhyay, S. (2020). A Privacy-Preserving Efficient Location-Sharing Scheme for Mobile Online Social Network Applications. IEEE Access, 8, 221330 - 221351. https://doi.org/10.1109/ACCESS.2020.3043621
• Wang, H., Ho, E. S., Shum, H. P., & Zhu, Z. (2019). Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling. IEEE Transactions on Visualization and Computer Graphics, https://doi.org/10.1109/tvcg.2019.2936810
• Rueangsirarak, W., Zhang, J., Aslam, N., Ho, E. S., & Shum, H. P. (2018). Automatic Musculoskeletal and Neurological Disorder Diagnosis With Relative Joint Displacement From Human Gait. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(12), 2387-2396. https://doi.org/10.1109/tnsre.2018.2880871
• Zhang, J., Shum, H. P., Han, J., & Shao, L. (2018). Action Recognition From Arbitrary Views Using Transferable Dictionary Learning. IEEE Transactions on Image Processing, 27(10), 4709-4723. https://doi.org/10.1109/tip.2018.2836323
• Zhang, L., Shum, H. P., & Shao, L. (2017). Manifold Regularized Experimental Design for Active Learning. IEEE Transactions on Image Processing, 26(2), 969-981. https://doi.org/10.1109/tip.2016.2635440
• Liu, Z., Zhou, L., Leung, H., & Shum, H. P. (2016). Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models. IEEE Transactions on Visualization and Computer Graphics, 22(11), 2437-2450. https://doi.org/10.1109/tvcg.2015.2510000
• Zhang, L., Shum, H., & Shao, L. (2016). Discriminative Semantic Subspace Analysis for Relevance Feedback. IEEE Transactions on Image Processing, 25(3), 1275-1287. https://doi.org/10.1109/tip.2016.2516947
• Henry, J., Shum, H. P., & Komura, T. (2014). Interactive Formation Control in Complex Environments. IEEE Transactions on Visualization and Computer Graphics, 20(2), 211-222. https://doi.org/10.1109/tvcg.2013.116
• Shum, H. P., Ho, E. S., Jiang, Y., & Takagi, S. (2013). Real-Time Posture Reconstruction for Microsoft Kinect. IEEE Transactions on Cybernetics, 43(5), 1357-1369. https://doi.org/10.1109/tcyb.2013.2275945
• Shum, H. P., Komura, T., & Yamazaki, S. (2012). Simulating Multiple Character Interactions with Collaborative and Adversarial Goals. IEEE Transactions on Visualization and Computer Graphics, 18(5), 741-752. https://doi.org/10.1109/tvcg.2010.257
• Shum, H. P., Komura, T., Shiraishi, M., & Yamazaki, S. (2008). Interaction patches for multi-character animation. ACM Transactions on Graphics, 27(5), Article 114. https://doi.org/10.1145/1409060.1409067