EAN: 9783031006968

SYNTHESIS LECTURES ON COMPUTER VISION MULTI-M...

For the last ten years  face biometric research has been intensively studied by the computer
vision community. Face recognition systems have been used in mobile  banking  and surveillance
systems. For face recognition systems  face spoofing attack detection is a crucial stage that
could cause severe security issues in government sectors. Although effective methods for face
presentation attack detection have been proposed so far  the problem is still unsolved due to
the difficulty in the design of features and methods that can work for new spoofing attacks. In
addition  existing datasets for studying the problem are relatively small which hinders the
progress in this relevant domain. In order to attract researchers to this important field and
push the boundaries of the state of the art on face anti-spoofing detection  we organized the
Face Spoofing Attack Workshop and Competition at CVPR 2019  an event part of the ChaLearn
Looking at People Series. As part of this event  we released the largest multi-modal face
anti-spoofing dataset so far  the CASIA-SURF benchmark. The workshop reunited many researchers
from around the world and the challenge attracted more than 300 teams. Some of the novel
methodologies proposed in the context of the challenge achieved state-of-the-art performance.
In this manuscript  we provide a comprehensive review on face anti-spoofing techniques
presented in this joint event and point out directions for future research on the face
anti-spoofing field.

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