@inproceedings{b9c0a8fb053048228ad821fe281fb3a6,
title = "Face Detection in Painting Using Deep Convolutional Neural Networks",
abstract = "The artistic style of paintings constitutes an important information about the painter{\textquoteright}s technique. It can provide a rich description of this technique using image processing tools, and particularly using image features. In this paper, we investigate automatic face detection in the Tenebrism style, a particular painting style that is characterized by the use of extreme contrast between the light and dark. We show that convolutional neural network along with an adapted learning base makes it possible to detect faces with a maximum accuracy in this style. This result is particularly interesting since it can be the basis of an illuminant study in the Tenebrism style.",
keywords = "Deep learning, Face detection, Illumination comprehension, Realist art",
author = "Olfa Mzoughi and Andr{\'e} Bigand and Christophe Renaud",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.; 19th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2018 ; Conference date: 24-09-2018 Through 27-09-2018",
year = "2018",
doi = "10.1007/978-3-030-01449-0\_28",
language = "English",
isbn = "9783030014483",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "333--341",
editor = "Jacques Blanc-Talon and Dan Popescu and Wilfried Philips and David Helbert and Paul Scheunders",
booktitle = "Advanced Concepts for Intelligent Vision Systems - 19th International Conference, ACIVS 2018, Proceedings",
address = "Germany",
}