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)
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)
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)
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: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 01 Mar 2022 13:01 |
| Last Modified: | 23 Sep 2022 19:52 |
| URI: | http://repository.essex.ac.uk/id/eprint/32428 |
Available files
Filename: Memorability_overview_2021.pdf
Licence: Creative Commons: Attribution 3.0