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Launched in 2013, LivDet-Iris is an international competition
series open to academia and industry with the aim to assess
and report advances in iris Presentation Attack Detection
(PAD). This paper presents results from the fourth
competition of the series: LivDet-Iris 2020. This year's
competition introduced several novel elements: (a)
incorporated new types of attacks (samples displayed on a
screen, cadaver eyes and prosthetic eyes), (b) initiated
LivDet-Iris as an on-going effort, with a testing protocol
available now to everyone via the Biometrics Evaluation and
Testing (BEAT)* open-source platform to facilitate
reproducibility and benchmarking of new algorithms
continuously, and (c) performance comparison of the
submitted entries with three baseline methods (offered by
the University of Notre Dame and Michigan State University),
and three open-source iris PAD methods available in the
public domain. The best performing entry to the competition
reported a weighted average APCER of 59.10% and a
BPCER of 0.46% over all five attack types. This paper
serves as the latest evaluation of iris PAD on a large
spectrum of presentation attack instruments
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