English
Related papers

Related papers: Overview of The MediaEval 2021 Predicting Media Me…

200 papers

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…

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

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

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…

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

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

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…

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

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

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

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

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

Video memorability refers to the ability of videos to be recalled after viewing, playing a crucial role in creating content that remains memorable. Existing models typically focus on extracting multimodal features to predict video…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Zhiyi Zhu , Xiaoyu Wu , Youwei Lu

While existing video benchmarks largely consider specialized downstream tasks like retrieval or question-answering (QA), contemporary multimodal AI systems must be capable of well-rounded common-sense reasoning akin to human visual…

Computer Vision and Pattern Recognition · Computer Science 2024-06-17 Kate Sanders , Benjamin Van Durme

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. This study delves into the elusive "moment of…

Neurons and Cognition · Quantitative Biology 2023-10-02 Lorin Sweeney , Graham Healy , Alan F. Smeaton

Sports video analysis is a prevalent research topic due to the variety of application areas, ranging from multimedia intelligent devices with user-tailored digests up to analysis of athletes' performance. The Sports Video task is part of…

Computer Vision and Pattern Recognition · Computer Science 2021-12-22 Pierre-Etienne Martin , Jordan Calandre , Boris Mansencal , Jenny Benois-Pineau , Renaud Péteri , Laurent Mascarilla , Julien Morlier

This paper introduces a new challenge and datasets to foster research toward designing systems that can understand medical videos and provide visual answers to natural language questions. We believe medical videos may provide the best…

Computer Vision and Pattern Recognition · Computer Science 2022-02-01 Deepak Gupta , Kush Attal , Dina Demner-Fushman

There has been significant attention to the research on dense video captioning, which aims to automatically localize and caption all events within untrimmed video. Several studies introduce methods by designing dense video captioning as a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Minkuk Kim , Hyeon Bae Kim , Jinyoung Moon , Jinwoo Choi , Seong Tae Kim
‹ Prev 1 2 3 10 Next ›