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State of the Art of Quality Assessment of Facial Images
The goal of the project "Facial Metrics for EES" is to develop, implement and publish an open source algorithm for the quality assessment of facial images (OFIQ) for face recognition, in particular for border control scenarios. 1 In order to stimulate the harmonization of the requirements and practices applied for QA for facial images, the insights gained and algorithms developed in the project will be contributed to the current (2022) revision of the ISO/IEC 29794-5 standard.
Face Beneath the Ink: Synthetic Data and Tattoo Removal with Application to Face Recognition
Moreover, we demonstrate the feasibility of the generation by using a deep learning-based model for removing tattoos from face images.
Crowd-powered Face Manipulation Detection: Fusing Human Examiner Decisions
To this end, various decision fusion methods are proposed incorporating the examiners' decision confidence, experience level, and their time to take a decision.
Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations
In recent years, increasing deployment of face recognition technology in security-critical settings, such as border control or law enforcement, has led to considerable interest in the vulnerability of face recognition systems to attacks utilising legitimate documents, which are issued on the basis of digitally manipulated face images.
Reliable Detection of Doppelgängers based on Deep Face Representations
Doppelg\"angers (or lookalikes) usually yield an increased probability of false matches in a facial recognition system, as opposed to random face image pairs selected for non-mated comparison trials.
An Attack on Facial Soft-biometric Privacy Enhancement
Future works on privacy-enhancing face recognition are encouraged to include the proposed attack in evaluations on the privacy protection.
Differential Anomaly Detection for Facial Images
Due to their convenience and high accuracy, face recognition systems are widely employed in governmental and personal security applications to automatically recognise individuals.
Feature Fusion Methods for Indexing and Retrieval of Biometric Data: Application to Face Recognition with Privacy Protection
Protection of the biometric probe templates, as well as the stored reference templates and the created index is carried out using homomorphic encryption.
Demographic Fairness in Face Identification: The Watchlist Imbalance Effect
Recently, different researchers have found that the gallery composition of a face database can induce performance differentials to facial identification systems in which a probe image is compared against up to all stored reference images to reach a biometric decision.
Demographic Fairness in Biometric Systems: What do the Experts say?
Algorithmic decision systems have frequently been labelled as "biased", "racist", "sexist", or "unfair" by numerous media outlets, organisations, and researchers.
Impact of Facial Tattoos and Paintings on Face Recognition Systems
In this work, we investigate the impact that facial tattoos and paintings have on current face recognition systems.
Signal-level Fusion for Indexing and Retrieval of Facial Biometric Data
The growing scope, scale, and number of biometric deployments around the world emphasise the need for research into technologies facilitating efficient and reliable biometric identification queries.
Biometrics in the Era of COVID-19: Challenges and Opportunities
Since early 2020 the COVID-19 pandemic has had a considerable impact on many aspects of daily life.
Detection of Makeup Presentation Attacks based on Deep Face Representations
Facial cosmetics have the ability to substantially alter the facial appearance, which can negatively affect the decisions of a face recognition.
