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In this paper, we present the Predicting Media Memorability task, which is proposed as part of the MediaEval 2018 Benchmarking Initiative for Multimedia Evaluation. Participants are expected to design systems that automatically predict…

Computer Vision and Pattern Recognition · Computer Science 2018-07-04 Romain Cohendet , Claire-Hélène Demarty , Ngoc Duong , Mats Sjöberg , Bogdan Ionescu , Thanh-Toan Do , France Rennes

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…

Neurons and Cognition · Quantitative Biology 2022-01-04 Lorin Sweeney , Ana Matran-Fernandez , Sebastian Halder , Alba G. Seco de Herrera , Alan Smeaton , Graham Healy

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…

With the explosion of video content on the Internet, there is a need for research on methods for video analysis which take human cognition into account. One such cognitive measure is memorability, or the ability to recall visual content…

Computer Vision and Pattern Recognition · Computer Science 2017-08-29 Sumit Shekhar , Dhruv Singal , Harvineet Singh , Manav Kedia , Akhil Shetty

This paper describes the MediaEval 2020 \textit{Predicting Media Memorability} task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and…

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. This year we tackle…

Computer Vision and Pattern Recognition · Computer Science 2021-12-16 Lorin Sweeney , Graham Healy , Alan F. Smeaton

Memorability determines what evanesces into emptiness, and what worms its way into the deepest furrows of our minds. It is the key to curating more meaningful media content as we wade through daily digital torrents. The Predicting Media…

Multimedia · Computer Science 2021-01-01 Lorin Sweeney , Graham Healy , Alan F. Smeaton

The Predicting Media Memorability task in MediaEval'20 has some challenging aspects compared to previous years. In this paper we identify the high-dynamic content in videos and dataset of limited size as the core challenges for the task, we…

Multimedia · Computer Science 2021-01-01 Phuc H. Le-Khac , Ayush K. Rai , Graham Healy , Alan F. Smeaton , Noel E. O'Connor

This paper describes the 5th edition of the Predicting Video Memorability Task as part of MediaEval2022. This year we have reorganised and simplified the task in order to lubricate a greater depth of inquiry. Similar to last year, two…

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. This has allowed us to compare the performance of many…

Modeling media memorability has been a consistent challenge in the field of machine learning. The Predicting Media Memorability task in MediaEval2020 is the latest benchmark among similar challenges addressing this topic. Building upon…

Machine Learning · Computer Science 2021-02-03 Tony Zhao , Irving Fang , Jeffrey Kim , Gerald Friedland

A key capability of an intelligent system is deciding when events from past experience must be remembered and when they can be forgotten. Towards this goal, we develop a predictive model of human visual event memory and how those memories…

Computer Vision and Pattern Recognition · Computer Science 2020-09-08 Anelise Newman , Camilo Fosco , Vincent Casser , Allen Lee , Barry McNamara , Aude Oliva

Humans share a strong tendency to memorize/forget some of the visual information they encounter. This paper focuses on providing computational models for the prediction of the intrinsic memorability of visual content. To address this new…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Romain Cohendet , Claire-Hélène Demarty , Ngoc Q. K. Duong , Martin Engilberge

Diffusion models have revolutionized generative modeling, enabling unprecedented realism in image and video synthesis. This success has sparked interest in leveraging their representations for visual understanding tasks. While recent works…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Pedro Vélez , Luisa F. Polanía , Yi Yang , Chuhan Zhang , Rishabh Kabra , Anurag Arnab , Mehdi S. M. Sajjadi

Visual content on social media plays a key role in entertainment and information sharing, yet some images gain more engagement than others. We propose that image memorability - the ability to be remembered - may predict viral potential.…

Human-Computer Interaction · Computer Science 2025-09-30 Shikang Peng , Wilma A. Bainbridge

Various work has suggested that the memorability of an image is consistent across people, and thus can be treated as an intrinsic property of an image. Using computer vision models, we can make specific predictions about what people will…

Computer Vision and Pattern Recognition · Computer Science 2022-01-11 Coen D. Needell , Wilma A. Bainbridge

Video anticipation is the task of predicting one/multiple future representation(s) given limited, partial observation. This is a challenging task due to the fact that given limited observation, the future representation can be highly…

Computer Vision and Pattern Recognition · Computer Science 2020-10-12 Sadegh Aliakbarian

Behavioral studies have shown that the memorability of images is similar across groups of people, suggesting that memorability is a function of the intrinsic properties of images, and is unrelated to people's individual experiences and…

Computer Vision and Pattern Recognition · Computer Science 2023-01-23 Thomas Hagen , Thomas Espeseth

Image memorability refers to the phenomenon where certain images are more likely to be remembered than others. It is a quantifiable and intrinsic image attribute, defined as the likelihood of an image being remembered upon a single…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Elham Bagheri , Yalda Mohsenzadeh

The pixels in an image, and the objects, scenes, and actions that they compose, determine whether an image will be memorable or forgettable. While memorability varies by image, it is largely independent of an individual observer. Observer…

Computer Vision and Pattern Recognition · Computer Science 2021-04-05 Zoya Bylinskii , Lore Goetschalckx , Anelise Newman , Aude Oliva
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