activity
20142026
most citedContrastive Representation Learning: A Framework and Review

855 citations · 941 across the 19 of their papers we have counts for

collaborators

20 papers

cs.CL2026

Encoding EEG Signals to Examine Human-Like Next-Word Prediction Behaviour in Language Models

Boi Mai Quach, Binh T. Nguyen, Cathal Gurrin +1

Language models (LMs) are trained to excel at predicting the next word in the sequence given prior context, and humans also share this predictability in reading comprehension. Neur…

q-bio.NC2023

Memories in the Making: Predicting Video Memorability with Encoding Phase EEG

Lorin Sweeney, Graham Healy, Alan F. Smeaton

In a world of ephemeral moments, our brain diligently sieves through a cascade of experiences, like a skilled gold prospector searching for precious nuggets amidst the river's rele…

cs.CV2022★ 1 cited

Diffusing Surrogate Dreams of Video Scenes to Predict Video Memorability

Lorin Sweeney, Graham Healy, Alan F. Smeaton

As part of the MediaEval 2022 Predicting Video Memorability task we explore the relationship between visual memorability, the visual representation that characterises it, and the u…

cs.CV2022★ 5 cited

Overview of The MediaEval 2022 Predicting Video Memorability Task

Lorin Sweeney, Mihai Gabriel Constantin, Claire-Hélène Demarty +8

This paper describes the 5th edition of the Predicting Video Memorability Task as part of MediaEval2022. This year we have reorganised and simplified the task in order to lubricate…

cs.CV2022

Experiences from the MediaEval Predicting Media Memorability Task

Alba García Deco de Herrera, Mihai Gabriel Constantin, Chaire-Hélène Demarty +8

The Predicting Media Memorability task in the MediaEval evaluation campaign has been running annually since 2018 and several different tasks and data sets have been used in this ti…

cs.LG2022

An Improved Subject-Independent Stress Detection Model Applied to Consumer-grade Wearable Devices

Van-Tu Ninh, Manh-Duy Nguyen, Sinéad Smyth +4

Stress is a complex issue with wide-ranging physical and psychological impacts on human daily performance. Specifically, acute stress detection is becoming a valuable application i…

q-bio.NC2021

Overview of the EEG Pilot Subtask at MediaEval 2021: Predicting Media Memorability

Lorin Sweeney, Ana Matran-Fernandez, Sebastian Halder +3

The aim of the Memorability-EEG pilot subtask at MediaEval'2021 is to promote interest in the use of neural signals -- either alone or in combination with other data sources -- in…

cs.CV2021★ 2 cited

Predicting Media Memorability: Comparing Visual, Textual and Auditory Features

Lorin Sweeney, Graham Healy, Alan F. Smeaton

This paper describes our approach to the Predicting Media Memorability task in MediaEval 2021, which aims to address the question of media memorability by setting the task of autom…

cs.CV2021★ 2 cited

Overview of The MediaEval 2021 Predicting Media Memorability Task

Rukiye Savran Kiziltepe, Mihai Gabriel Constantin, Claire-Helene Demarty +8

This paper describes the MediaEval 2021 Predicting Media Memorability}task, which is in its 4th edition this year, as the prediction of short-term and long-term video memorability…

cs.MM2021★ 6 cited

The Influence of Audio on Video Memorability with an Audio Gestalt Regulated Video Memorability System

Lorin Sweeney, Graham Healy, Alan F. Smeaton

Memories are the tethering threads that tie us to the world, and memorability is the measure of their tensile strength. The threads of memory are spun from fibres of many modalitie…

cs.MM2020

Investigating Memorability of Dynamic Media

Phuc H. Le-Khac, Ayush K. Rai, Graham Healy +2

The Predicting Media Memorability task in MediaEval'20 has some challenging aspects compared to previous years. In this paper we identify the high-dynamic content in videos and dat…

cs.MM2020

Leveraging Audio Gestalt to Predict Media Memorability

Lorin Sweeney, Graham Healy, Alan F. Smeaton

Memorability determines what evanesces into emptiness, and what worms its way into the deepest furrows of our minds. It is the key to curating more meaningful media content as we w…

cs.LG2020★ 855 cited

Contrastive Representation Learning: A Framework and Review

Phuc H. Le-Khac, Graham Healy, Alan F. Smeaton

Contrastive Learning has recently received interest due to its success in self-supervised representation learning in the computer vision domain. However, the origins of Contrastive…

cs.MM2020★ 5 cited

Keystroke Dynamics as Part of Lifelogging

Alan F. Smeaton, Naveen Garaga Krishnamurthy, Amruth Hebbasuru Suryanarayana

In this paper we present the case for including keystroke dynamics in lifelogging. We describe how we have used a simple keystroke logging application called Loggerman, to create a…

cs.CV2020★ 2 cited

A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Zhengwei Wang, Qi She, Alan F. Smeaton +2

Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. However, eva…

cs.CV2019★ 5 cited

Synthetic-Neuroscore: Using A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Zhengwei Wang, Qi She, Alan F. Smeaton +2

Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. Arguably the…

eess.IV2019★ 11 cited

Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation

Zhengwei Wang, Graham Healy, Alan F. Smeaton +1

Rapid Serial Visual Presentation (RSVP) is a paradigm that supports the application of cortically coupled computer vision to rapid image search. In RSVP, images are presented to pa…

cs.CV2018★ 35 cited

Use of Neural Signals to Evaluate the Quality of Generative Adversarial Network Performance in Facial Image Generation

Zhengwei Wang, Graham Healy, Alan F. Smeaton +1

There is a growing interest in using generative adversarial networks (GANs) to produce image content that is indistinguishable from real images as judged by a typical person. A num…

cs.HC2015

Exploring EEG for Object Detection and Retrieval

Eva Mohedano, Amaia Salvador, Sergi Porta +5

This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based image retrieval. We investigate if it is possible to…

cs.CV2014★ 12 cited

Object Segmentation in Images using EEG Signals

Eva Mohedano, Graham Healy, Kevin McGuinness +3

This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the i…