Staff profile

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

Prof. Hubert P. H. Shum is a Professor of Visual Computing and the Director of Research of the Department of Computer Science at Durham University, specialising in modelling spatio-temporal information with responsible AI. He has authored over 180 research publications in the fields of Computer Vision, Computer Graphics, Machine Learning and Biomedical Engineering, covering major venues such as CVPR, ICCV, ECCV, SIGGRAPH, MICCAI, IEEE TVCG, IEEE TIP and IEEE TMM.

His research is fundamental to many disciplines, facilitating him to engage in multidisciplinary research related to healthcare, space technology and art. He is a Co-Founder and the Co-Director of Durham University Space Research 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. He is an Advisory Board member of TORUS, a £6 mil EPSRC project supporting Parkinson's disease patients with sensing technologies.

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 establish a new digital health hub in 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, France, China, 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 the Computer Graphics Forum, a Guest Editor for the International Journal of Computer Vision, and a Program Committee member in over 20 conferences such as Eurographics and Pacific Graphics. He also has also served in the EPSRC Peer Review College and has frequently review grant proposals from EPSRC, Mitacs, ANR, NSERC, FCT.

Joining Us

Follow the application instructions to join us either as a PhD student, a visiting/internship student, or an academic visitor. My team has a supportive culture with members developing high-quality research while enjoying their vibrant lives in the UK.

PhD directions include:

• Computer Vision with Responsible Artificial Intelligence for Human-Related Data
• Deep Learning Based Machine Vision for Space-Informed Applications
• Artificial Intelligence for Virtual Characters in Computer Graphics and Computer Animation

Recent Research

• Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising (IEEE Transactions on Visualization and Computer Graphics)

• HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention (IEEE Transactions on Multimedia)

• A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis (IEEE Transactions on Visualization and Computer Graphics)

• Hierarchical Graph Convolutional Networks for Action Quality Assessment (IEEE Transactions on Circuits and Systems for Video Technology)

• Interaction-Aware Decision-Making for Automated Vehicles using Social Value Orientation (IEEE Transactions on Intelligent Vehicles)

• Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation (Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition)

• Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient (Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision)

• Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers (Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision)

• 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)

• Geometric Features Informed Multi-Person Human-Object Interaction Recognition in Videos (Proceedings of the 2022 European Conference on Computer Vision)

• Pose-Based Tremor Classification for Parkinson’s Disease Diagnosis from Video (Proceedings of the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention)

• 360 Depth Estimation in the Wild - The Depth360 Dataset and the SegFuse Network (Proceedings of the 2022 IEEE Conference on Virtual Reality and 3D User Interfaces)

Research Grants

• Durham University Strategy Research Fund, "Durham University Space Research Centre", Co-Founder and Co-Investigator, Department of Computer Science Leader, £2.76 million
• 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
• 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

Professional Activities

Conference Services

• Conference Chair of the Pacific Conference on Computer Graphics and Applications 2022
• Conference Chair of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation 2022
• Conference Chair of the ACM SIGGRAPH Conference on Motion, Interaction and Games 2019
• Program Chair of the British Machine Vision Conference 2018
• Program Chair of the International Conference on Software, Knowledge, Information Management and Applications 2018
• Program Chair of the ACM SIGGRAPH Conference on Motion in Games 2016
• Area Chair of the British Machine Vision Conference 2023, 2022, 2021 and 2020

Journal Editorships

• Computer Graphics Forum (CGF), Associate Editor, 2019 - 2023
• International Journal of Computer Vision (IJCV), Guest Editor, Special Issue on Machine Vision and Deep Learning, 2020

Awards

• Best Paper Award in the IEEE/CVF Conference on Computer Vision and Pattern Recognition DCAMI Workshop, 2024
• Exceptional Achievement for Excellence in PhD Supervision by Durham University in 2023
• Exceptional Achievement for Excellence in Teaching by Durham University in 2022
• Best Paper Award in the IEEE International Conference on Human-Machine Systems 2021
• Best Student Paper Award in the International Conference on Computer Graphics Theory and Applications (GRAPP) 2020
• Best Poster Award in the ACM SIGGRAPH Conference on Motion, Interaction and Games (MIG) 2019
• Best Paper Award in the International Conference on Advances in Computer Entertainment Technology (ACE) 2017
• Best Poster Award in the ACM SIGGGRAPH Conference on Motion in Games (MIG) 2016

Media Coverage

• Interviewed by the UK Catapult Network on how AI and computer vision enhance security, 2023

• 2000: Director of Research, Department of Computer Science:

Chapter in book

• Vijendran, M., Li, F. W. B., Deng, J., & Shum, H. P. H. (in press). ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification. In CCIS '24: Communications in Computer and Information Science. Springer

Conference Paper

• Corona-Figueroa, A., Shum, H. P. H., & Willcocks, C. G. (2024, June). Repeat and Concatenate: 2D to 3D Image Translation with 3D to 3D Generative Modeling. Presented at 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington
• Chen, S., Atapour-Abarghouei, A., Zhang, H., & Shum, H. P. H. (2024, November). MxT: Mamba x Transformer for Image Inpainting. Presented at BMVC 2024: The 35th British Machine Vision Conference, Glasgow, UK
• Liu, R., Remagnino, P., & Shum, H. P. (2024, December). Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration. Presented at 2024 International Conference on Pattern Recognition, Kolkata, India
• Qiao, T., Li, R., Li, F. W. B., & Shum, H. P. H. (2024, December). From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos. Presented at Proceedings of the 2024 International Conference on Pattern Recognition, Kolkata, India, 2024., Kolkata, India
• Li, L., Qiao, T., Shum, H. P. H., & Breckon, T. P. (2024, November). TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training. Presented at BMVC'24: The 35th British Machine Vision Conference, Glasgow, UK
• Chen, S., Zhang, H., Atapour-Abarghouei, A., & Shum, H. P. H. (2025, February). SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM. Presented at 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona
• Xiatian Zhang, F., Chen, S., Xie, X., & Shum, H. P. (2024, October). Depth-Aware Endoscopic Video Inpainting. Presented at 27th International Conference on Medical Image Computing and Computer Assisted Intervention, Marrakesh, Morocco
• Zhou, K., Wang, L., Zhang, X., Shum, H. P. H., Li, F. W. B., Li, J., & Liang, X. (2024, September). MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment. Presented at ECCV 2024: The 18th European Conference on Computer Vision, Milan, Italy
• Li, L., Shum, H. P. H., & Breckon, T. P. (2024, September). RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation. Presented at ECCV 2024: European Conference on Computer Vision, Milan, Italy
• Li, B., Ho, E. S. L., Shum, H. P. H., & Wang, H. (2024, June). Two-Person Interaction Augmentation with Skeleton Priors. Presented at 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, Washington
• Liu, M., Frawley, J., Wyer, S., Shum, H. P. H., Uckelman, S. L., Black, S., & Willcocks, C. G. (2024, June). Self-Regulated Sample Diversity in Large Language Models. Presented at NAACL 2024: 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Mexico City
• Liu, J., Yu, Z., Breckon, T. P., & Shum, H. P. H. (2024, January). U3DS3 : Unsupervised 3D Semantic Scene Segmentation. Presented at 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA
• Crosato, L., Wei, C., Ho, E. S. L., Shum, H. P. H., & Sun, Y. (2024, March). A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection. Presented at 2024 ACM/IEEE International Conference on Human Robot Interaction (HRI '24), Boulder, CO, USA
• Zhou, K., Chen, C., Ma, Y., Leng, Z., Shum, H. P., Li, F. W., & Liang, X. (2023, October). A Mixed Reality Training System for Hand-Object Interaction in Simulated Microgravity Environments. Presented at ISMAR 23: International Symposium on Mixed and Augmented Reality, Sydney, Australia
• Feng, Q., Shum, H. P., & Morishima, S. (2023, October). Enhancing Perception and Immersion in Pre-Captured Environments through Learning-Based Eye Height Adaptation. Presented at ISMAR 23: International Symposium on Mixed and Augmented Reality, Sydney, Australia
• Zhang, X., Zheng, S., Shum, H. P., Zhang, H., Song, N., Song, M., & Jia, H. (2023, November). Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRI. Presented at ICONIP 2023: 2023 International Conference on Neural Information Processing, Changsha, China
• Vijendran, M., Li, F. W., & Shum, H. P. (2023, February). Tackling Data Bias in Painting Classification with Style Transfer. Presented at VISAPP '23: 2023 International Conference on Computer Vision Theory and Applications, Lisbon, Portugal
• Lu, Z., Wang, H., Chang, Z., Yang, G., & Shum, H. P. (2023, October). Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient. Presented at ICCV 2023: 2023 IEEE/CVF International Conference on Computer Vision (ICCV), Paris, France
• Corona-Figueroa, A., Bond-Taylor, S., Bhowmik, N., Gaus, Y. F. A., Breckon, T. P., Shum, H. P., & Willcocks, C. G. (2023, October). Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers. Presented at ICCV23: 2023 IEEE/CVF International Conference on Computer Vision, Paris, France
• Gaus, Y., Bhowmik, N., Issac-Medina, B., Atapour-Abarghouei, A., Shum, H., & Breckon, T. (2023, June). Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023, Vancouver, BC
• Chang, Z., Findlay, E. J., Zhang, H., & Shum, H. P. (2023, February). Unifying Human Motion Synthesis and Style Transfer with Denoising Diffusion Probabilistic Models. Presented at GRAPP 2023: 2023 International Conference on Computer Graphics Theory and Applications, Lisbon, Portugal
• Li, L., Shum, H. P., & Breckon, T. P. (2023, June). Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation. Presented at 2023 IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), Vancouver, BC
• Chang, Z., Koulieris, G. A., & Shum, H. P. (2022, November). 3D Reconstruction of Sculptures from Single Images via Unsupervised Domain Adaptation on Implicit Models. Presented at VRST '22: 28th ACM Symposium on Virtual Reality Software and Technology, Japan
• Li, R., Katsigiannis, S., & Shum, H. P. (2022, October). Multiclass-SGCN: Sparse Graph-based Trajectory Prediction with Agent Class Embedding. Presented at ICIP 2022: IEEE International Conference in Image Processing, Bordeaux, France
• Chen, S., Atapour-Abarghouei, A., Kerby, J., Ho, E. S., Sainsbury, D. C., Butterworth, S., & Shum, H. P. (2022, September). A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip. Presented at 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Ioannina, Greece
• Organisciak, D., Poyser, M., Alsehaim, A., Hu, S., Isaac-Medina, B. K., Breckon, T. P., & Shum, H. P. UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery. Presented at 2022 17th International Conference on Computer Vision Theory and Applications
• Feng, Q., Shum, H. P., & Morishima, S. (2022, March). 360 Depth Estimation in the Wild - The Depth360 Dataset and the SegFuse Network. Presented at IEEE Conference on Virtual Reality and 3D User Interfaces, Christchurch, New Zealand
• Zhang, X., Zhang, H., & Shum, H. P. (2022, September). Pose-based Tremor Classification for Parkinson’s Disease Diagnosis from Video. Presented at MICCAI '22: The 25th International Conference on Medical Image Computing and Computer Assisted Intervention, Singapore
• Corona-Figueroa, A., Frawley, J., Bond-Taylor, S., Bethapudi, S., Shum, H. P., & Willcocks, C. G. (2022, July). MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray. Presented at 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Glasgow, Scotland
• Qiao, T., Men, Q., Li, F. W., Kubotani, Y., Morishima, S., & Shum, H. P. (2022, October). Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos. Presented at Computer Vision - ECCV 2022, Tel Aviv, Israel
• Zhang, X., Al Moubayed, N., & Shum, H. P. (2022, September). Towards Graph Representation Learning Based Surgical Workflow Anticipation. Presented at 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Ioannina, Greece
• Li, L., Ismail, K. N., Shum, H. P., & Breckon, T. P. (2021, December). DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications. Presented at International Conference on 3D Vision, Surrey / Online
• Leng, Z., Chen, J., Shum, H. P., Li, F. W., & Liang, X. (2021, March). Stable Hand Pose Estimation under Tremor via Graph Neural Network. Presented at 2021 IEEE Virtual Reality and 3D User Interfaces (VR), Lisboa
• Zhou, K., Cheng, Z., Shum, H. P., Li, F. W., & Liang, X. (2021, October). STGAE: Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising. Presented at 2021 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Bari, Italy
• Isaac-Medina, B. K., Poyser, M., Organisciak, D., Willcocks, C. G., Breckon, T. P., & Shum, H. P. (2021, October). Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark. Presented at 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Montreal, BC, Canada

Journal Article

• Zhou, K., Ma, Y., Shum, H. P., & Liang, X. (online). Hierarchical Graph Convolutional Networks for Action Quality Assessment. IEEE Transactions on Circuits and Systems for Video Technology, 33(12), 7749 - 7763. https://doi.org/10.1109/TCSVT.2023.3281413
• Constable, M. D., Zhang, F. X., Conner, T., Monk, D., Rajsic, J., Ford, C., Park, L. J., Platt, A., Porteous, D., Grierson, L., & Shum, H. P. H. (online). Advancing healthcare practice and education via data sharing: demonstrating the utility of open data by training an artificial intelligence model to assess cardiopulmonary resuscitation skills. Advances in Health Sciences Education, https://doi.org/10.1007/s10459-024-10369-5
• Zhu, M., Ho, E. S. L., Chen, S., Yang, L., & Shum, H. P. H. (2024). Geometric Features Enhanced Human-Object Interaction Detection. IEEE Transactions on Instrumentation and Measurement, 73, Article 5026014. https://doi.org/10.1109/TIM.2024.3427800
• Zheng, S., Zhang, F. X., Shum, H. P. H., Zhang, H., Song, N., Song, M., & Jia, H. (2024). Unraveling the brain dynamics of Depersonalization-Derealization Disorder: a dynamic functional network connectivity analysis. BMC Psychiatry, 24, Article 685. https://doi.org/10.1186/s12888-024-06096-1
• Fan, H., Qin, X., Chen, S., Shum, H. P. H., & Li, M. (2024). One-Index Vector Quantization Based Adversarial Attack on Image Classification. Pattern Recognition Letters, 186, 47-56. https://doi.org/10.1016/j.patrec.2024.09.001
• Zhang, H., Ho, E. S. L., Zhang, X., Del Din, S., & Shum, H. P. H. (2024). Pose-based tremor type and level analysis for Parkinson’s disease from video. International Journal of Computer Assisted Radiology and Surgery, 19(5), 831-840. https://doi.org/10.1007/s11548-023-03052-4
• Chen, S., Atapour-Abarghouei, A., & Shum, H. P. H. (2024). HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention. IEEE Transactions on Multimedia, 26, 7649-7660. https://doi.org/10.1109/TMM.2024.3369897
• Constable, M. D., Shum, H. P. H., & Clark, S. (2024). Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review. Journal of Cardiothoracic Surgery, 19(1), Article 94. https://doi.org/10.1186/s13019-024-02558-5
• Crosato, L., Tian, K., Shum, H. P., Ho, E. S., Wang, Y., & Wei, C. (2023). Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles. Advanced Intelligent Systems, 6(3), Article 2300575. https://doi.org/10.1002/aisy.202300575
• Zhou, K., Shum, H. P., Li, F. W., & Liang, X. (2023). Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising. IEEE Transactions on Visualization and Computer Graphics, https://doi.org/10.1109/TVCG.2023.3337868
• 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., Shum, H. P., Li, F. W., Jin, S., & 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., Munteanu, A., & 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
• Wang, H., Ho, E. S., Shum, H. P., & Zhu, Z. (2021). Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling. IEEE Transactions on Visualization and Computer Graphics, 27(1), 216 - 227. https://doi.org/10.1109/tvcg.2019.2936810
• 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., Guo, J., & 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
• 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
• Shen, Y., Henry, J., Wang, H., Ho, E. S., Komura, T., & Shum, H. P. (2018). Data-Driven Crowd Motion Control With Multi-Touch Gestures. Computer Graphics Forum, 37(6), 382-394. https://doi.org/10.1111/cgf.13333
• Plantard, P., Shum, H. P., Le Pierres, A.-S., & Multon, F. (2017). Validation of an ergonomic assessment method using Kinect data in real workplace conditions. Applied Ergonomics: Human Factors in Technology and Society, 65, 562-569. https://doi.org/10.1016/j.apergo.2016.10.015
• 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
• Ho, E. S., Shum, H. P., Cheung, Y.-M., & Yuen, P. (2013). Topology Aware Data-Driven Inverse Kinematics. Computer Graphics Forum, 32(7), 61-70. https://doi.org/10.1111/cgf.12212
• 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