MediaEval 2018: Predicting Media Memorability

Romain Cohendet; Claire Hélène Demarty; Ngoc Q.K. Duong; Mats Sjöberg; Bogdan Ionescu; Thanh-Toan Do

MediaEval 2018: Predicting Media Memorability

Romain Cohendet, Claire Hélène Demarty, Ngoc Q.K. Duong, Mats Sjöberg, Bogdan Ionescu, Thanh-Toan Do

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

Abstract

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 memorability scores for videos, which reflect the probability of a video being remembered. In contrast to previous work in image memorability prediction, where memorability was measured a few minutes after memorization, the proposed dataset comes with "short-term" and "long-term" memorability annotations. All task characteristics are described, namely: the task's challenges and breakthrough, the released data set and ground truth, the required runs and the evaluation metrics. Copyright held by the owner/author(s).

Original language	English
Title of host publication	Working Notes Proceedings of the MediaEval 2018 Workshop
Editors	Martha Larson, Piyush Arora, Claire-Hélène Demarty, Michael Riegler, Benjamin Bischke, Emmanuel Dellandrea, Mathias Lux, Alastair Porter, Gareth J.F. Jones
Place of Publication	Aachen Germany
Publisher	CEUR-WS
Number of pages	3
Volume	2283
Publication status	Published - 2018
Externally published	Yes
Event	Working Notes Proceedings of the MediaEval Workshop 2018 - Sophia Antipolis, France Duration: 29 Oct 2018 → 31 Oct 2018 http://ceur-ws.org/Vol-2283/ (Proceedings)

Publication series

Name	CEUR Workshop Proceedings
Publisher	CEUW - WS
ISSN (Print)	1613-0073

Conference

Conference	Working Notes Proceedings of the MediaEval Workshop 2018
Abbreviated title	MediaEval 2018
Country	France
City	Sophia Antipolis
Period	29/10/18 → 31/10/18
Internet address	http://ceur-ws.org/Vol-2283/ (Proceedings)

Access to Document

330559612-oaFinal published version, 416 KB

Cite this

Cohendet, R., Demarty, C. H., Duong, N. Q. K., Sjöberg, M., Ionescu, B., & Do, T-T. (2018). MediaEval 2018: Predicting Media Memorability. In M. Larson, P. Arora, C-H. Demarty, M. Riegler, B. Bischke, E. Dellandrea, M. Lux, A. Porter, & G. J.F. Jones (Eds.), Working Notes Proceedings of the MediaEval 2018 Workshop (Vol. 2283). (CEUR Workshop Proceedings). CEUR-WS. http://ceur-ws.org/Vol-2283/MediaEval_18_paper_1.pdf

Cohendet, Romain ; Demarty, Claire Hélène ; Duong, Ngoc Q.K. ; Sjöberg, Mats ; Ionescu, Bogdan ; Do, Thanh-Toan. / MediaEval 2018 : Predicting Media Memorability. Working Notes Proceedings of the MediaEval 2018 Workshop. editor / Martha Larson ; Piyush Arora ; Claire-Hélène Demarty ; Michael Riegler ; Benjamin Bischke ; Emmanuel Dellandrea ; Mathias Lux ; Alastair Porter ; Gareth J.F. Jones. Vol. 2283 Aachen Germany : CEUR-WS, 2018. (CEUR Workshop Proceedings).

@inproceedings{b4f47ff08eca41958d4f2c16954b7259,

title = "MediaEval 2018: Predicting Media Memorability",

abstract = "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 memorability scores for videos, which reflect the probability of a video being remembered. In contrast to previous work in image memorability prediction, where memorability was measured a few minutes after memorization, the proposed dataset comes with {"}short-term{"} and {"}long-term{"} memorability annotations. All task characteristics are described, namely: the task's challenges and breakthrough, the released data set and ground truth, the required runs and the evaluation metrics. Copyright held by the owner/author(s).",

author = "Romain Cohendet and Demarty, {Claire H{\'e}l{\`e}ne} and Duong, {Ngoc Q.K.} and Mats Sj{\"o}berg and Bogdan Ionescu and Thanh-Toan Do",

year = "2018",

language = "English",

volume = "2283",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS",

editor = "Larson, {Martha } and Arora, {Piyush } and Demarty, {Claire-H{\'e}l{\`e}ne } and Riegler, {Michael } and Bischke, {Benjamin } and Dellandrea, {Emmanuel } and Lux, {Mathias } and Porter, {Alastair } and {J.F. Jones}, Gareth",

booktitle = "Working Notes Proceedings of the MediaEval 2018 Workshop",

note = "Working Notes Proceedings of the MediaEval Workshop 2018, MediaEval 2018 ; Conference date: 29-10-2018 Through 31-10-2018",

url = "http://ceur-ws.org/Vol-2283/",

}

Cohendet, R, Demarty, CH, Duong, NQK, Sjöberg, M, Ionescu, B & Do, T-T 2018, MediaEval 2018: Predicting Media Memorability. in M Larson, P Arora, C-H Demarty, M Riegler, B Bischke, E Dellandrea, M Lux, A Porter & G J.F. Jones (eds), Working Notes Proceedings of the MediaEval 2018 Workshop. vol. 2283, CEUR Workshop Proceedings, CEUR-WS, Aachen Germany, Working Notes Proceedings of the MediaEval Workshop 2018, Sophia Antipolis, France, 29/10/18. <http://ceur-ws.org/Vol-2283/MediaEval_18_paper_1.pdf>

MediaEval 2018 : Predicting Media Memorability. / Cohendet, Romain; Demarty, Claire Hélène; Duong, Ngoc Q.K.; Sjöberg, Mats; Ionescu, Bogdan; Do, Thanh-Toan.

Working Notes Proceedings of the MediaEval 2018 Workshop. ed. / Martha Larson; Piyush Arora; Claire-Hélène Demarty; Michael Riegler; Benjamin Bischke; Emmanuel Dellandrea; Mathias Lux; Alastair Porter; Gareth J.F. Jones. Vol. 2283 Aachen Germany : CEUR-WS, 2018. (CEUR Workshop Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

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