Spoofing Face Recognition With 3D Masks

By Nesli Erdogmus, Sébastien Marcel. IEEE Transactions on Information Forensics and Security, 2014

319 citations recorded by the source corpus.

How researchers see this paper

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A review of convolutional neural network architectures and their optimizations (2022, background): “For example, face recognition models are vulnerable to spoofing attacks in some security protection tasks (Erdogmus and Marcel 2014; Costa-Pazo et al.”
Design of an Active Multispectral SWIR Camera System for Skin Detection and Face Verification (2016, background): “Face recognition is a very important aspect for biometric systems and a very active research topic [1].”
Learning One Class Representations for Face Presentation Attack Detection Using Multi-Channel Convolutional Neural Networks (2020, background): “been proposed over the years [11]–[15], [30]–[32] to achieve reliable PAD performance.”
Secure Face Unlock: Spoof Detection on Smartphones (2016, background): “Since then, a number of methods have been proposed for face spoofing detection under print attacks [4], [6], [8], [10], replay attacks [3], [9], [40], and 3D mask attacks [41].”
Biometric Antispoofing Methods: A Survey in Face Recognition (2014, methodology): “The 3D MASK-ATTACK DB [107], [109] is publicly available at the IDIAP Research Institute website.”
Face Anti-Spoofing: Model Matters, so Does Data (2019, background): “Face anti-spoofing [40, 1, 15, 14] is an important, yet challenging problem in the face recognition community.”