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Authors: Iurii Medvedev 1 ; Farhad Shadmand 1 and Nuno Gonçalves 1 ; 2

Affiliations: 1 Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal ; 2 Portuguese Mint and Official Printing Office (INCM), Lisbon, Portugal

Keyword(s): Face Morphing Detection, Face Recognition, Deep Learning, Convolutional Neural Networks, Classification.

Abstract: Face morphing attack detection (MAD) is one of the most challenging tasks in the field of face recognition nowadays. In this work, we introduce a novel deep learning strategy for a single image face morphing detection, which implies the discrimination of morphed face images along with a sophisticated face recognition task in a complex classification scheme. It is directed onto learning the deep facial features, which carry information about the authenticity of these features. Our work also introduces several additional contributions: the public and easy-to-use face morphing detection benchmark and the results of our wild datasets filtering strategy. Our method, which we call MorDeephy, achieved the state of the art performance and demonstrated a prominent ability for generalizing the task of morphing detection to unseen scenarios.

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Paper citation in several formats:
Medvedev, I.; Shadmand, F. and Gonçalves, N. (2023). MorDeephy: Face Morphing Detection via Fused Classification. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-626-2; ISSN 2184-4313, SciTePress, pages 193-204. DOI: 10.5220/0011606100003411

@conference{icpram23,
author={Iurii Medvedev. and Farhad Shadmand. and Nuno Gon\c{C}alves.},
title={MorDeephy: Face Morphing Detection via Fused Classification},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2023},
pages={193-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011606100003411},
isbn={978-989-758-626-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - MorDeephy: Face Morphing Detection via Fused Classification
SN - 978-989-758-626-2
IS - 2184-4313
AU - Medvedev, I.
AU - Shadmand, F.
AU - Gonçalves, N.
PY - 2023
SP - 193
EP - 204
DO - 10.5220/0011606100003411
PB - SciTePress

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