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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

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…

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

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 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

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

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

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.…

Computer Vision and Pattern Recognition · Computer Science 2022-12-20 Lorin Sweeney , Graham Healy , Alan F. Smeaton

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

Using a collection of publicly available links to short form video clips of an average of 6 seconds duration each, 1,275 users manually annotated each video multiple times to indicate both long-term and short-term memorability of the…

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

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

Nowadays, humans are constantly exposed to music, whether through voluntary streaming services or incidental encounters during commercial breaks. Despite the abundance of music, certain pieces remain more memorable and often gain greater…

Information Retrieval · Computer Science 2024-05-22 Li-Yang Tseng , Tzu-Ling Lin , Hong-Han Shuai , Jen-Wei Huang , Wen-Whei Chang

Image memorability, i.e., how likely an image is to be remembered, has traditionally been studied in computer vision either as a passive prediction task, with models regressing a scalar score, or with generative methods altering the visual…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Francesco Laiti , Davide Talon , Jacopo Staiano , Elisa Ricci

Given the massive market of advertising and the sharply increasing online multimedia content (such as videos), it is now fashionable to promote advertisements (ads) together with the multimedia content. It is exhausted to find relevant ads…

Multimedia · Computer Science 2020-01-06 Huaizheng Zhang , Yong Luo , Qiming Ai , Yonggang Wen

As humans, we can remember certain visuals in great detail, and sometimes even after viewing them once. What is even more interesting is that humans tend to remember and forget the same things, suggesting that there might be some general…

Computer Vision and Pattern Recognition · Computer Science 2023-01-19 Ananya Sadana , Nikita Thakur , Nikita Poria , Astika Anand , Seeja K. R

Effective summarisation evaluation metrics enable researchers and practitioners to compare different summarisation systems efficiently. Estimating the effectiveness of an automatic evaluation metric, termed meta-evaluation, is a critically…

Computation and Language · Computer Science 2024-10-01 Xiang Dai , Sarvnaz Karimi , Biaoyan Fang

In the competitive landscape of advertising, success hinges on effectively navigating and leveraging complex interactions among consumers, advertisers, and advertisement platforms. These multifaceted interactions compel advertisers to…

Artificial Intelligence · Computer Science 2025-02-26 Sepehr Asgarian , Qayam Jetha , Jouhyun Jeon
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