activity
20182021
most citedMulti-Level Sequence GAN for Group Activity Recognition

4 citations · 7 across the 4 of their papers we have counts for

collaborators

10 papers

eess.IV2021

Multi-Slice Net: A novel light weight framework for COVID-19 Diagnosis

Harshala Gammulle, Tharindu Fernando, Sridha Sridharan +2

This paper presents a novel lightweight COVID-19 diagnosis framework using CT scans. Our system utilises a novel two-stage approach to generate robust and efficient diagnoses acros…

cs.LG2020

Deep Learning for Medical Anomaly Detection -- A Survey

Tharindu Fernando, Harshala Gammulle, Simon Denman +2

Machine learning-based medical anomaly detection is an important problem that has been extensively studied. Numerous approaches have been proposed across various medical applicatio…

cs.CV2020

Multi-modal Fusion for Single-Stage Continuous Gesture Recognition

Harshala Gammulle, Simon Denman, Sridha Sridharan +1

Gesture recognition is a much studied research area which has myriad real-world applications including robotics and human-machine interaction. Current gesture recognition methods h…

cs.CV2020

Two-Stream Deep Feature Modelling for Automated Video Endoscopy Data Analysis

Harshala Gammulle, Simon Denman, Sridha Sridharan +1

Automating the analysis of imagery of the Gastrointestinal (GI) tract captured during endoscopy procedures has substantial potential benefits for patients, as it can provide diagno…

cs.CV2020

Hierarchical Attention Network for Action Segmentation

Harshala Gammulle, Simon Denman, Sridha Sridharan +1

The temporal segmentation of events is an essential task and a precursor for the automatic recognition of human actions in the video. Several attempts have been made to capture fra…

cs.CV20193 cited

Predicting the Future: A Jointly Learnt Model for Action Anticipation

Harshala Gammulle, Simon Denman, Sridha Sridharan +1

Inspired by human neurological structures for action anticipation, we present an action anticipation model that enables the prediction of plausible future actions by forecasting bo…