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.
@article{arxiv.2112.05982,
title = {Overview of The MediaEval 2021 Predicting Media Memorability Task},
author = {Rukiye Savran Kiziltepe and Mihai Gabriel Constantin and Claire-Helene Demarty and Graham Healy and Camilo Fosco and Alba Garcia Seco de Herrera and Sebastian Halder and Bogdan Ionescu and Ana Matran-Fernandez and Alan F. Smeaton and Lorin Sweeney},
journal= {arXiv preprint arXiv:2112.05982},
year = {2021}
}
Comments
3 pages, to appear in Proceedings of MediaEval 2021, December 13-15 2021, Online