Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data Call for Papers
Call for competition participation -
IJCB 2022 -
Competition on
Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data
IJCB-SYN-MAD-2022
Competition website: https://sites.google.com/view/ijcb-syn-mad-2022
IJCB2022 website: https://ijcb2022.org/
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A face morphing attack aims at creating images that automatically or
by human experts are matched to faces of more than one
individual. When morphing attacks are used in travel or identity
documents, they allow multiple subjects to be verified to one
document. This faulty subject link can lead to a wide range of illegal
activities and lead to the development of morphing attack detection
(MAD) algorithms. However, most of the existing MAD solutions are
based on bona fide and attack images of real individuals and raise
various privacy concerns as well as limit the amount of publicly
available data for research.
This competition is the first to attract and present technical
solutions that enhance the accuracy of morphing attack detection and
it is the first competition on presentation attack detection to be
restricted to synthetic training data.
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All participants, who achieve competitive results, will be invited as
co-authors for the summary paper of this competition. The competition
summary paper will be submitted to the International Joint Conference
on Biometrics (IJCB) 2022.
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Schedule:
16. March 2022: Call for participation, website release, and registration open.
28. April 2022: Deadline for registration
30. April 2022: Deadline for algorithm submission
15. May 2022: Announcement of the results to the participants
31. May 2022: Submission of competition summary paper to IJCB 2022
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Competition Organizers
Marco Huber - Fraunhofer Institute for Computer Graphics Research IGD,
Germany and TU Darmstadt, Germany
Fadi Boutrous - Fraunhofer Institute for Computer Graphics Research
IGD, Germany and TU Darmstadt, Germany
Kiran Raja - Norwegian University of Science and Technology, Norway
Raghavendra Ramachandra - Norwegian University of Science and
Technology, Norway
Naser Damer -
Fraunhofer Institute for Computer Graphics Research IGD, Germany
and TU Darmstadt, Germany