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Using Saliency and Cropping to Improve Video Memorability
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.
Memories in the Making: Predicting Video Memorability with Encoding Phase EEG
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.
Diffusing Surrogate Dreams of Video Scenes to Predict Video Memorability
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.
Overview of The MediaEval 2022 Predicting Video Memorability Task
This paper describes the 5th edition of the Predicting Video Memorability Task as part of MediaEval2022.
Experiences from the MediaEval Predicting Media Memorability Task
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.
Analysing the Memorability of a Procedural Crime-Drama TV Series, CSI
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.
Overview of the EEG Pilot Subtask at MediaEval 2021: Predicting Media Memorability
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.
Predicting Media Memorability: Comparing Visual, Textual and Auditory Features
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.
Overview of The MediaEval 2021 Predicting Media Memorability Task
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.
An Annotated Video Dataset for Computing Video Memorability
Data includes the reaction times for each recognition of each video.
The Influence of Audio on Video Memorability with an Audio Gestalt Regulated Video Memorability System
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.
Leveraging Audio Gestalt to Predict Media Memorability
Memorability determines what evanesces into emptiness, and what worms its way into the deepest furrows of our minds.
