Predicting media memorability with audio, video, and text representations

Reboud, Alison; Harrando, Ismail; Laaksonen, Jorma; Troncy, Raphaël
MEDIAEVAL 2020, Multimedia Evaluation Benchmark, 14-15 December 2020, Virtual Event

This paper describes a multimodal approach proposed by the MeMAD team for the MediaEval 2020 “Predicting Media Memorability” task. Our best approach is a weighted average method combining predictions made separately from visual, audio, textual and visiolinguistic representations of videos. Our best model achieves Spearman scores of 0.101 and 0.078, respectively, for the short and long term predictions tasks.


Type:
Conférence
Date:
2020-12-14
Department:
Data Science
Eurecom Ref:
6438
Copyright:
CEUR

PERMALINK : https://www.eurecom.fr/publication/6438