Image memorability using diverse visual features and soft attention

5Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In this paper we present a method for still image memorability estimation. The proposed solution exploits feature maps extracted from two Convolutional Neural Networks pre-trained for object recognition and memorability estimation respectively. The feature maps are then enhanced using a soft attention mechanism in order to let the model focus on highly informative image regions for memorability estimation. Results achieved on a benchmark dataset demonstrate the effectiveness of the proposed method.

Cite

CITATION STYLE

APA

Leonardi, M., Celona, L., Napoletano, P., Bianco, S., Schettini, R., Manessi, F., & Rozza, A. (2019). Image memorability using diverse visual features and soft attention. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11752 LNCS, pp. 171–180). Springer Verlag. https://doi.org/10.1007/978-3-030-30645-8_16

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free