Sébastien Marcel

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Publications associées (51)

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CNN Patch Pooling for Detecting 3D Mask Presentation Attacks in NIR

Sébastien Marcel

Presentation attacks using 3D masks pose a serious threat to face recognition systems. Automatic detection of these attacks is challenging due to hyper-realistic nature of masks. In this work, we consider presentations acquired in near infrared (NIR) imagi ...

IEEE2020

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

Sébastien Marcel, Amir Mohammadi

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

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

Feature distribution modelling techniques for 3D face recognition

Sébastien Marcel

This paper shows that Hidden Markov Models (HMMs) can be effectively ap- plied to 3D face data. The examined HMM techniques are shown to be superior to a previously examined Gaussian Mixture Model (GMM) technique. Experi- ments conducted on the Face Recogn ...

2010

Multi-IVE: Privacy Enhancement of Multiple Soft-Biometrics in Face Embeddings

Sébastien Marcel, Hatef Otroshi Shahreza

This study focuses on the protection of soft-biometric attributes related to the demographic information of individuals that can be extracted from compact representations of face images, called embeddings. We consider a state-ofthe-art technology for soft- ...

IEEE COMPUTER SOC2023

A Fast Parts-based Approach to Speaker Verification using Boosted Slice Classifiers

Sébastien Marcel, Mathew Magimai Doss, Anindya Roy

Speaker verification on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, possibl ...

2012

Supervised domain adaptation for text-independent speaker verification using limited data

Sébastien Marcel, Petr Motlicek

ISCA2020

Cross Modal Focal Loss for RGBD Face Anti-Spoofing

Sébastien Marcel

Automatic methods for detecting presentation attacks are essential to ensure the reliable use of facial recognition technology. Most of the methods available in the litera- ture for presentation attack detection (PAD) fails in gen- eralizing to unseen atta ...

IEEE2021

Session variability modelling for face authentication

Sébastien Marcel, Laurent El Shafey

This study examines session variability modelling for face authentication using Gaussian mixture models. Session variability modelling aims to explicitly model and suppress detrimental within-class (inter-session) variation. The authors examine two techniq ...

2013

Face Reconstruction Fromdeep Facial Embeddings Using A Convolutional Neural Network

Sébastien Marcel, Hatef Otroshi Shahreza

State-of-the-art (SOTA) face recognition systems generally use deep convolutional neural networks (CNNs) to extract deep features, called embeddings, from face images. The face embeddings are stored in the system's database and are used for recognition of ...

IEEE2022

Face liveness detection using dynamic texture

Sébastien Marcel, André Anjos, Tiago De Freitas Pereira

User authentication is an important step to protect information, and in this context, face biometrics is potentially advantageous. Face biometrics is natural, intuitive, easy to use, and less human-invasive. Unfortunately, recent work has revealed that fac ...

2014