Outputs (134)
Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language (2023)
Presentation / Conference Contribution
Sign languages enable effective communication between deaf and hearing people. Despite years of extensive pedagogical research, learning sign language online comes with a number of difficulties that might be frustrating for some students. Indeed, mos... Read More about Exploring the Potential of Immersive Virtual Environments for Learning American Sign Language.
Anomaly Detection with Transformers in Face Anti-spoofing (2023)
Presentation / Conference Contribution
Transformers are emerging as the new gold standard in various computer vision applications, and have already been used in face anti-spoofing demonstrating competitive performance. In this paper, we propose a network with the ViT transformer and ResNe... Read More about Anomaly Detection with Transformers in Face Anti-spoofing.
Seeing Through the Data: A Statistical Evaluation of Prohibited Item Detection Benchmark Datasets for X-ray Security Screening (2023)
Presentation / Conference Contribution
The rapid progress in automatic prohibited object detection within the context of X-ray security screening, driven forward by advances in deep learning, has resulted in the first internationally-recognized, application-focused object detection perfor... Read More about Seeing Through the Data: A Statistical Evaluation of Prohibited Item Detection Benchmark Datasets for X-ray Security Screening.
An Inverted Pyramid Acceleration Structure Guiding Foveated Sphere Tracing for Implicit Surfaces in VR (2023)
Presentation / Conference Contribution
Improving Health Mention Classification through Emphasising Literal Meanings: a Study Towards Diversity and Generalisation for Public Health Surveillance (2023)
Presentation / Conference Contribution
Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery (2023)
Presentation / Conference Contribution
Anomaly detection is a classical problem within automated visual surveillance, namely the determination of the normal from the abnormal when operational data availability is highly biased towards one class (normal) due to both insufficient sample siz... Read More about Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery.
Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption (2023)
Presentation / Conference Contribution
Anomaly detection is the task of recognising novel samples which deviate significantly from pre-established normality. Abnormal classes are not present during training meaning that models must learn effective representations solely across normal clas... Read More about Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption.
Tackling Data Bias in Painting Classification with Style Transfer (2023)
Presentation / Conference Contribution
It is difficult to train classifiers on paintings collections due to model bias from domain gaps and data bias from the uneven distribution of artistic styles. Previous techniques like data distillation, traditional data augmentation and style transf... Read More about Tackling Data Bias in Painting Classification with Style Transfer.
Unifying Human Motion Synthesis and Style Transfer with Denoising Diffusion Probabilistic Models (2023)
Presentation / Conference Contribution
Generating realistic motions for digital humans is a core but challenging part of computer animations and games, as human motions are both diverse in content and rich in styles. While the latest deep learning approaches have made significant advancem... Read More about Unifying Human Motion Synthesis and Style Transfer with Denoising Diffusion Probabilistic Models.
Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields (2023)
Presentation / Conference Contribution
Neural Radiance Fields (NeRF) have attracted significant attention due to their ability to synthesize novel scene views with great accuracy. However, inherent to their underlying formulation, the sampling of points along a ray with zero width may res... Read More about Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields.
Predicting the Performance of a Computing System with Deep Networks (2023)
Presentation / Conference Contribution
Predicting the performance and energy consumption of computing hardware is critical for many modern applications. This will inform procurement decisions, deployment decisions, and autonomic scaling. Existing approaches to understanding the performanc... Read More about Predicting the Performance of a Computing System with Deep Networks.
Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets (2022)
Presentation / Conference Contribution
A Virtual Reality System for the Assessment of Patients with Lower Limb Rotational Abnormalities (2023)
Presentation / Conference Contribution
Rotational lower limb abnormalities cause patellar mal-tracking which impacts young patients. Repetitive patellar dislocation may require knee arthroplasty. Surgeons employ CT to identify rotational abnormalities and make surgical decisions. Recent s... Read More about A Virtual Reality System for the Assessment of Patients with Lower Limb Rotational Abnormalities.
Recurrent neural networks for financial time-series modelling (2018)
Presentation / Conference Contribution
Conversational interaction recognition based on bodily and facial movement (2014)
Presentation / Conference Contribution
Labeling subtle conversational interactions within the CONVERSE dataset (2017)
Presentation / Conference Contribution