Publication

Analysis of Head Mounted Wireless Camera Videos for Early Diagnosis of Autism

Publications associées (22)

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Touradj Ebrahimi, Lin Yuan, Xiao Pu, Hongbo Li, Yao Zhang

The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Ieee-Inst Electrical Electronics Engineers Inc2024

The autism susceptibility kinase, TAOK2, phosphorylates eEF2 and modulates translation

Nagammal Neelagandan

Genes implicated in translation control have been associated with autism spectrum disorders (ASDs). However, some important genetic causes of autism, including the 16p11.2 microdeletion, bear no obvious connection to translation. Here, we use proteomics, g ...

Amer Assoc Advancement Science2024

Towards Visual Saliency Explanations of Face Verification

Touradj Ebrahimi, Yuhang Lu, Zewei Xu

In the past years, deep convolutional neural networks have been pushing the frontier of face recognition (FR) techniques in both verification and identification scenarios. Despite the high accuracy, they are often criticized for lacking explainability. The ...

2024

Discriminative Deep Feature Visualization for Explainable Face Recognition

Touradj Ebrahimi, Yuhang Lu, Zewei Xu

Despite the huge success of deep convolutional neural networks in face recognition (FR) tasks, current methods lack explainability for their predictions because of their ``black-box'' nature. In recent years, studies have been carried out to give an interp ...

2023

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

Explanation of Face Recognition via Saliency Maps

Touradj Ebrahimi, Yuhang Lu

Despite the significant progress in recent years, deep face recognition is often treated as a "black box" and has been criticized for lacking explainability. It becomes increasingly important to understand the characteristics and decisions of deep face rec ...

2023

Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups

Sébastien Marcel, Christophe René Joseph Ecabert, Parsa Rahimi Noshanagh

Recently, it has been exposed that some modern facial recognition systems could discriminate specific demographic groups and may lead to unfair attention with respect to various facial attributes such as gender and origin. The main reason are the biases in ...

IEEE2023

Are GAN-based Morphs Threatening Face Recognition?

Sébastien Marcel, Eklavya Sarkar, Laurent Colbois

Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access control ...

IEEE2022

A Novel Framework for Assessment of Deep Face Recognition Systems in Realistic Conditions

Touradj Ebrahimi, Luca Barras, Yuhang Lu

Deep convolutional neural networks have shown remarkable results on face recognition (FR). Despite their significant progress, the performance of current face recognition techniques is often assessed in benchmarks under not always realistic conditions. The ...

2022

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

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

Poly-NL: Linear Complexity Non-local Layers With 3rd Order Polynomials

Filippos Kokkinos, Grigorios Chrysos

Spatial self-attention layers, in the form of Non-Local blocks, introduce long-range dependencies in Convolutional Neural Networks by computing pairwise similarities among all possible positions. Such pairwise functions underpin the effectiveness of non-lo ...

IEEE2021

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

A Graph Signal Processing Framework for the Classification of Temporal Brain Data

Ntorina Thanou, Sarah Itani

Graph Signal Processing (GSP) addresses the analysis of data living on an irregular domain which can be modeled with a graph. This capability is of great interest for the study of brain connectomes. In this case, data lying on the nodes of the graph are co ...

IEEE2020

Multi-Modal Recurrent Attention Networks for Facial Expression Recognition

Jiyoung Lee, Seungryong Kim

Recent deep neural networks based methods have achieved state-of-the-art performance on various facial expression recognition tasks. Despite such progress, previous researches for facial expression recognition have mainly focused on analyzing color recordi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

ExprADA: Adversarial domain adaptation for facial expression analysis

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

2020

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

Generating Master Faces for Use in PerformingWolf Attacks on Face Recognition Systems

Sébastien Marcel

Due to its convenience, biometric authentication, especial face authentication, has become increasingly mainstream and thus is now a prime target for attackers. Presentation attacks and face morphing are typical types of attack. Previous research has shown ...

IEEE2020

Learn to synthesize and synthesize to learn

Jean-Philippe Thiran, Mohammad Saeed Rad, Hazim Kemal Ekenel, Seyedbehzad Bozorgtabar

Attribute guided face image synthesis aims to manipulate attributes on a face image. Most existing methods for image-to-image translation can either perform a fixed translation between any two image domains using a single attribute or require training data ...

2019

Learning How To Recognize Faces In Heterogeneous Environments

Tiago De Freitas Pereira

Face recognition is a mature field in biometrics in which several systems have been proposed over the last three decades. Such systems are extremely reliable under controlled recording conditions and it has been deployed in the field in critical tasks, suc ...

EPFL2019