In this paper we propose an approach based on deep Convolutional Neural Networks (CNNs) to recognize artistic photo filters applied to images. A total of 22 types of Instagram-like filters is considered. Different CNN architectures taken from the image recognition literature are compared on a dataset of more than 0.46 M images from the Places-205 dataset. Experimental results show that not only it is possible to reliably determine whether or not one of these filters has been applied, but also which one. Differently from other tasks, where the fine-tuning of a CNN trained on a different problem is usually good enough, here the fine-tuned AlexNet obtains an accuracy of only 67.5%. We show, instead, that an accuracy of about 99.0% can be obtained by training a CNN from scratch for this specific problem.

Bianco, S., Cusano, C., Schettini, R. (2017). Artistic photo filtering recognition using cnns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.249-258). Springer Verlag [10.1007/978-3-319-56010-6_21].

Artistic photo filtering recognition using cnns

BIANCO, SIMONE
;
CUSANO, CLAUDIO
Secondo
;
SCHETTINI, RAIMONDO
Ultimo
2017

Abstract

In this paper we propose an approach based on deep Convolutional Neural Networks (CNNs) to recognize artistic photo filters applied to images. A total of 22 types of Instagram-like filters is considered. Different CNN architectures taken from the image recognition literature are compared on a dataset of more than 0.46 M images from the Places-205 dataset. Experimental results show that not only it is possible to reliably determine whether or not one of these filters has been applied, but also which one. Differently from other tasks, where the fine-tuning of a CNN trained on a different problem is usually good enough, here the fine-tuned AlexNet obtains an accuracy of only 67.5%. We show, instead, that an accuracy of about 99.0% can be obtained by training a CNN from scratch for this specific problem.
slide + paper
Theoretical Computer Science; Computer Science (all)
English
6th International Workshop on Computational Color Imaging, CCIW 2017
2017
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783319560090
2017
10213
249
258
http://springerlink.com/content/0302-9743/copyright/2005/
none
Bianco, S., Cusano, C., Schettini, R. (2017). Artistic photo filtering recognition using cnns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.249-258). Springer Verlag [10.1007/978-3-319-56010-6_21].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/154780
Citazioni
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 3
Social impact