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Amir Mohammadi

Related publications (11)

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Iris Liveness Detection Competition (LivDet-Iris) – The 2020 Edition

Sébastien Marcel, Amir Mohammadi, Priyanka Das

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 ...

IEEE2020

DOMAIN ADAPTATION FOR GENERALIZATION OF FACE PRESENTATION ATTACK DETECTION IN MOBILE SETTINGS WITH MINIMAL INFORMATION

Sébastien Marcel, Amir Mohammadi

With face-recognition (FR) increasingly replacing fingerprint sensors for user-authentication on mobile devices, presentation attacks (PA) have emerged as the single most significant hurdle for manufacturers of FR systems. Current machine-learning based pr ...

IEEE2020

Trustworthy Face Recognition: Improving Generalization of Deep Face Presentation Attack Detection

Amir Mohammadi

The extremely high recognition accuracy achieved by modern, convolutional neural network (CNN) based face recognition (FR) systems has contributed significantly to the adoption of such systems in a variety of applications, from mundane activities like unlo ...

EPFL2020

Biometric-based verification is widely employed on the smartphones for various applications, including financial transactions. In this work, we present a new multimodal biometric dataset (face, voice, and periocular) acquired using a smartphone. The new da ...

Idiap2020

Presentation attack detection (PAD) is now considered critically important for any face-recognition (FR) based access-control system. Current deep-learning based PAD systems show excellent performance when they are tested in intra-dataset scenarios. Under ...

IEEE2020

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Presentation attack detection (PAD, also known as anti-spoofing) systems, regardless of the technique, biometric mode or degree of independence of external equipment, are most commonly treated as binary classification systems. The two classes that they dif ...

Springer International Publishing2019

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The undeniable convenience of face-recognition (FR) based biometrics has made it an attractive tool for access control in various applications, from immigration-control to remote banking. Widespread adopti on of face biometrics, however, depends on the how ...

Springer2019

On Effectiveness of Anomaly Detection Approaches against Unseen Presentation Attacks in Face Anti-Spoofing

Sébastien Marcel, André Anjos, Amir Mohammadi

While face recognition systems got a significant boost in terms of recognition performance in recent years, they are known to be vulnerable to presentation attacks. Up to date, most of the research in the field of face anti-spoofing or presentation attack ...

2018

Continuously Reproducing Toolchains in Pattern Recognition and Machine Learning Experiments

Sébastien Marcel, André Anjos, Tiago De Freitas Pereira, Amir Mohammadi

Pattern recognition and machine learning research work often contains experimental results on real-world data, which corroborates hypotheses and provides a canvas for the development and comparison of new ideas. Results, in this context, are typically summ ...

2017

Deeply Vulnerable -- a study of the robustness of face recognition to presentation attacks

Sébastien Marcel, Amir Mohammadi

The vulnerability of deep-learning-based face-recognition (FR) methods, to presentation attacks (PA), is studied in this study. Recently, proposed FR methods based on deep neural networks (DNN) have been shown to outperform most other methods by a signific ...

Inst Engineering Technology-Iet2017