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Use of in-the-wild images for anomaly detection in face anti-spoofing
[article]
2020
arXiv
pre-print
The traditional approach to face anti-spoofing sees it as a binary classification problem, and binary classifiers are trained and validated on specialized anti-spoofing databases. One of the drawbacks of this approach is that, due to the variability of face spoofing attacks, environmental factors, and the typically small sample size, such classifiers do not generalize well to previously unseen databases. Anomaly detection, which approaches face anti-spoofing as a one-class classification
arXiv:2006.10626v1
fatcat:lh3s3abb6fgjnmoxwawxderoja