Publication
The 2013 Face Recognition Evaluation in Mobile Environment
Publications associées (47)
Performing and Detecting Backdoor Attacks on Face Recognition Algorithms
The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...
EPFL2024PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation
Touradj Ebrahimi, Lin Yuan, Xiao Pu, Yao Zhang, Hongbo Li
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 Inc2024Towards 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 ...
2023Recognizing distant faces
Lukas Vogelsang, Marin Vogelsang
As an 'early alerting' sense, one of the primary tasks for the human visual system is to recognize distant objects. In the specific context of facial identification, this ecologically important task has received surprisingly little attention. Most studies ...
PERGAMON-ELSEVIER SCIENCE LTD2023Discriminative 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 ...
2023A Novel Framework for Assessment of Deep Face Recognition Systems in Realistic Conditions
Touradj Ebrahimi, Yuhang Lu, Luca Barras
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 ...
2022On 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 ...
IEEE2021Model-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 ...
EPFL2021DOMAIN 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