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Overview of The MediaEval 2021 Predicting Media Memorability Task

Savran Kiziltepe, Rukiye and Constantin, Mihai Gabriel and Demarty, Claire-Hélène and Healy, Graham and Fosco, Camilo and Garcia Seco De Herrera, Alba and Halder, Sebastian and Ionescu, Bogdan and Matran-Fernandez, Ana and Smeaton, Alan F and Sweeney, Lorin (2021) Overview of The MediaEval 2021 Predicting Media Memorability Task. In: MediaEval Multimedia Evaluation benchmark (MediaEval), 2021-12-13 - 2021-12-15. (In Press)

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Abstract

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. In 2021, two datasets of videos are used: first, a subset of the TRECVid 2019 Video-to-Text dataset; second, the Memento10K dataset in order to provide opportunities to explore cross-dataset generalisation. In addition, an Electroencephalography (EEG)-based prediction pilot subtask is introduced. In this paper, we outline the main aspects of the task and describe the datasets, evaluation metrics, and requirements for participants’ submissions.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 01 Mar 2022 13:01
Last Modified: 01 Mar 2022 13:03
URI: http://repository.essex.ac.uk/id/eprint/32428

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