no code implementations • 21 Sep 2023 • Vaibhav Mudgal, Qingyang Wang, Lorin Sweeney, Alan F. Smeaton
Video memorability is a measure of how likely a particular video is to be remembered by a viewer when that viewer has no emotional connection with the video content.
no code implementations • 16 Aug 2023 • 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 relentless flow.
no code implementations • 19 Dec 2022 • 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 underlying concept portrayed by that visual representation.
no code implementations • 13 Dec 2022 • Lorin Sweeney, Mihai Gabriel Constantin, Claire-Hélène Demarty, Camilo Fosco, Alba G. Seco de Herrera, Sebastian Halder, Graham Healy, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Mushfika Sultana
This paper describes the 5th edition of the Predicting Video Memorability Task as part of MediaEval2022.
no code implementations • 7 Dec 2022 • Alba García Deco de Herrera, Mihai Gabriel Constantin, Chaire-Hélène Demarty, Camilo Fosco, Sebastian Halder, Graham Healy, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Mushfika Sultana, Lorin Sweeney
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 time.
no code implementations • 6 Aug 2022 • Sean Cummins, Lorin Sweeney, Alan F. Smeaton
We investigate the memorability of a 5-season span of a popular crime-drama TV series, CSI, through the application of a vision transformer fine-tuned on the task of predicting video memorability.
no code implementations • 15 Dec 2021 • 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 automatically predicting video memorability.
no code implementations • 15 Dec 2021 • Lorin Sweeney, Ana Matran-Fernandez, Sebastian Halder, Alba G. Seco de Herrera, Alan Smeaton, Graham Healy
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 the context of predicting video memorability by highlighting the utility of EEG data.
no code implementations • 11 Dec 2021 • Rukiye Savran Kiziltepe, Mihai Gabriel Constantin, Claire-Helene Demarty, Graham Healy, Camilo Fosco, Alba Garcia Seco de Herrera, Sebastian Halder, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Lorin Sweeney
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 remains a challenging task.
no code implementations • 4 Dec 2021 • Rukiye Savran Kiziltepe, Lorin Sweeney, Mihai Gabriel Constantin, Faiyaz Doctor, Alba Garcia Seco de Herrera, Claire-Helene Demarty, Graham Healy, Bogdan Ionescu, Alan F. Smeaton
Data includes the reaction times for each recognition of each video.
no code implementations • 23 Apr 2021 • Lorin Sweeney, Graham Healy, Alan F. Smeaton
We introduce a novel multimodal deep learning-based late-fusion system that uses audio gestalt to estimate the influence of a given video's audio on its overall short-term recognition memorability, and selectively leverages audio features to make a prediction accordingly.
no code implementations • 31 Dec 2020 • 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.