In this paper we investigate the use of a deep Convolutional Neural Network (CNN) to predict image aesthetics. To this end we finetune a canonical CNN architecture, originally trained to classify objects and scenes, by casting the image aesthetic prediction as a regression problem. We also investigate whether image aesthetic is a global or local attribute, and the role played by bottom-up and top-down salient regions to the prediction of the global image aesthetic. Experimental results on the canonical Aesthetic Visual Analysis (AVA) dataset show the robustness of the solution proposed, which outperforms the best solution in the state of the art by almost 17% in terms of Mean Residual Sum of Squares Error (MRSSE)

Bianco, S., Celona, L., Napoletano, P., Schettini, R. (2016). Predicting image aesthetics with deep learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.117-125). Springer Verlag [10.1007/978-3-319-48680-2_11].

Predicting image aesthetics with deep learning

BIANCO, SIMONE
Primo
;
CELONA, LUIGI
Secondo
;
NAPOLETANO, PAOLO
;
SCHETTINI, RAIMONDO
Ultimo
2016

Abstract

In this paper we investigate the use of a deep Convolutional Neural Network (CNN) to predict image aesthetics. To this end we finetune a canonical CNN architecture, originally trained to classify objects and scenes, by casting the image aesthetic prediction as a regression problem. We also investigate whether image aesthetic is a global or local attribute, and the role played by bottom-up and top-down salient regions to the prediction of the global image aesthetic. Experimental results on the canonical Aesthetic Visual Analysis (AVA) dataset show the robustness of the solution proposed, which outperforms the best solution in the state of the art by almost 17% in terms of Mean Residual Sum of Squares Error (MRSSE)
poster + paper
image aesthetics; deep learning
English
International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS - 24- 27 October
2016
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783319486796
2016
10016
117
125
none
Bianco, S., Celona, L., Napoletano, P., Schettini, R. (2016). Predicting image aesthetics with deep learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.117-125). Springer Verlag [10.1007/978-3-319-48680-2_11].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/136179
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