Hubert P. H. Shum

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Associate Professor in Computer Science, Deputy Director of Research

University of Durham

United Kingdom

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Hubert P. H. Shum is an Associate Professor in Computer Science and the Deputy Director of Research at Durham University, UK. His research interests include the development of advanced algorithms in artificial intelligence, particularly focusing on bias mitigation, diffusion models, and graph neural networks. Recent publications highlight his work on multi-person human-object interaction recognition, pedestrian trajectory prediction, and graph-based methodologies for action quality assessment.

Recent Grants

Grant: Close

Northern Health Futures Hub (NortHFutures)

Open Date: 2023-10-01

Close Date: 2026-09-01

Grant: Close

Skin Lesion Classification with Real-World Data

Open Date: 2023-01-01

Close Date: 2024-01-01

Grant: Close

Autonomous Persistent Wide Area Surveillance of Human and Vehicle Activity

Open Date: 2022-09-01

Close Date: 2023-05-01

Grant: Close

Tracking Drones Across Different Platforms with Machine Vision

Open Date: 2020-01-01

Close Date: 2021-01-01

Grant: Close

Modelling Human Motion for Synthesis and Recognition with Deep Learning on Surface Features

Open Date: 2019-12-01

Close Date: 2021-12-01

Hubert P. H. Shum

Research Interests

Explore related searches

Contact this professor

About

Recent Grants

Articles (26)

BOOST: Out-of-distribution-informed adaptive sampling for bias mitigation in stylistic convolutional neural networks

On the design fundamentals of diffusion models: A survey

Real‐Time and Controllable Reactive Motion Synthesis via Intention Guidance

Geometric visual fusion graph neural networks for multi-person human-object interaction recognition in videos

PHI: Bridging Domain Shift in Long-Term Action Quality Assessment via Progressive Hierarchical Instruction

BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction

Unified Spatial–Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction

Artificial intelligence for geometry-based feature extraction, analysis and synthesis in artistic images: a survey

MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment

Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review.

One-index vector quantization based adversarial attack on image classification

Geometric Features Enhanced Human–Object Interaction Detection

HINT: High-Quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention

Pose-based tremor type and level analysis for Parkinson’s disease from video

Social Interaction-Aware Dynamical Models and Decision-Making for Autonomous Vehicles

INCLG: Inpainting for non-cleft lip generation with a multi-task image processing network

Interaction-Aware Decision-Making for Automated Vehicles Using Social Value Orientation

A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis

Focalized contrastive view-invariant learning for self-supervised skeleton-based action recognition

Hierarchical Graph Convolutional Networks for Action Quality Assessment

Image editing-based data augmentation for illumination-insensitive background subtraction

CP-AGCN: Pytorch-based attention informed graph convolutional network for identifying infants at risk of cerebral palsy

A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction

3D car shape reconstruction from a contour sketch using GAN and lazy learning

GAN-based reactive motion synthesis with class-aware discriminators for human–human interaction

Collaborators (8)

Frederick W. B. Li

Qianhui MEN

Silvia Del Din

Tae-Kyun (T-K) Kim

Chongfeng Wei

Edmond S. L. Ho

Shigeo Morishima

Stephen Clark

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