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Dublin's participation in the predicting media memorability task at MediaEval 2018

Smeaton, Alan F. ORCID: 0000-0003-1028-8389, Corrigan, Owen ORCID: 0000-0002-1840-982X, Dockree, Paul, Gurrin, Cathal ORCID: 0000-0003-2903-3968, Healy, Graham ORCID: 0000-0001-6429-6339, Hu, Feiyan ORCID: 0000-0001-7451-6438, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Mohedano, Eva and Ward, Tomás E. ORCID: 0000-0002-6173-6607 (2018) Dublin's participation in the predicting media memorability task at MediaEval 2018. In: MediaEval Benchmarking Initiative for Multimedia Evaluation, 29-31 Oct 2018, Nice, France.

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Abstract

This paper outlines 6 approaches taken to computing video memorability, for the MediaEval media memorability task. The approaches are based on video features, an end-to-end approach, saliency, aesthetics, neural feedback, and an ensemble of all approaches.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:No
Subjects:Computer Science > Image processing
Computer Science > Digital video
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Research Initiatives and Centres > ADAPT
Published in: Larson, Martha and Arora, Piyush and Demarty, Claire-Hélène and Riegler, Michael and Bischke, Benjamin and Dellandrea, Emmanuel and Lux, Mathias and Porter, Alastair and Jones, Gareth J.F., (eds.) Working Notes Proceedings of the MediaEval 2018 Workshop. CEUR-WS Proceedings . CEUR-WS.
Publisher:CEUR-WS
Official URL:http://ceur-ws.org/Vol-2283/MediaEval_18_paper_14.pdf
Copyright Information:© 2018 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:This work was partially supported by Science Foundation Ireland under the SFI Research Centres Programme grant number SFI/12/RC/2289.
ID Code:22737
Deposited On:18 Oct 2018 09:27 by Owen Corrigan . Last Modified 13 Mar 2019 13:53

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