Concept

Face ID

Related publications (189)

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

On the Recognition Performance of BioHashing on state-of-the-art Face Recognition models

Sébastien Marcel, Hatef Otroshi Shahreza

Face recognition has become a popular authentication tool in recent years. Modern state-of-the-art (SOTA) face recognition methods rely on deep neural networks, which extract discriminative features from face images. Although these methods have high recogn ...

IEEE2021

Model-based 3D Face Reconstruction

Christophe René Joseph Ecabert

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

EPFL2021

Balancing of Coupled Piezoelectric NEMS Resonators

Luis Guillermo Villanueva Torrijo, Damien Maillard, Johannes Mathis Valentin Lemonde

Micro and Nano Electro Mechanical systems (M/NEMS) have a lot of potential to be used for sensing in different schemes and operation modes. We focus here on the use of coupled resonators for sensing and address the major limitation that these systems face, ...

FRONTIERS MEDIA SA2021

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

Can Your Face Detector Do Anti-spoofing? Face Presentation Attack Detection with a Multi-Channel Face Detector

Sébastien Marcel

In a typical face recognition pipeline, the task ofthe face detector is to localize the face region. However, the facedetector localizes regions that look like a face, irrespective of theliveliness of the face, which makes the entire system susceptible to ...

Idiap2020

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

On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing

Sébastien Marcel

The vulnerability of face recognition systems to presentation attacks has limited their application in security-critical scenarios. Automatic methods of detecting such malicious attempts are essential for the safe use of facial recognition technology. Alth ...

Idiap2020

Face Recognition Systems Under Spoofing Attacks

Sébastien Marcel, André Anjos, Ivana Chingovska

In this chapter we give an overview of spoofing attacks and spoofing counter-measures for face recognition systems, in particular in a verification sce- nario. We focus on 2D and 3D attacks to Visible Spectrum systems (VIS), as well as Near Infrared (NIR) ...

Idiap2020

IMPROVING CROSS-DATASET PERFORMANCE OF FACE PRESENTATION ATTACK DETECTION SYSTEMS USING FACE RECOGNITION DATASETS

Sébastien Marcel, Amir Mohammadi

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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