Overview of The MediaEval 2023 Predicting Video Memorability Task.

This paper describes the sixth edition of the Predicting Video Memorability task, part of the MediaEval1 multimedia evaluation benchmark initiative. Similar to previous editions, we use video data and annotations from two datasets, the Memento10k, and the VideoMem datasets. In light of the consistent performance plateau observed in previous iterations of the prediction task, in which participants were required to train and test on the same dataset, we have taken the decision to drop the prediction task from this year’s competition. This modification allows participants the opportunity to redirect their efforts toward more challenging tasks. Therefore, for this edition we propose two tasks: the generalization task, where participants are required to train on one dataset and test their results on a different dataset, and the EEG task, where participants are required to predict memorability using EEG-related data. In this paper we present the main aspects of the 2023 Predicting Video Memorability task, exploring the proposed tasks, the datasets, evaluation methods and metrics, as well as the requirements for participants.