17 citations · 38 across the 12 of their papers we have counts for
13 papers
PreFIQs: Face Image Quality Is What Survives Pruning
Jan Niklas Kolf, Guray Ozgur, Andrea Atzori +4
Face Image Quality Assessment (FIQA) evaluates the utility of a face image for automated face recognition (FR) systems. In this work, we propose PreFIQs, an unsupervised and traini…
EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment
Guray Ozgur, Tahar Chettaoui, Eduarda Caldeira +4
Face Image Quality Assessment is crucial for reliable face recognition systems, yet existing Vision Transformer-based approaches rely exclusively on final-layer representations, ig…
ATTN-FIQA: Interpretable Attention-based Face Image Quality Assessment with Vision Transformers
Guray Ozgur, Tahar Chettaoui, Eduarda Caldeira +5
Face Image Quality Assessment (FIQA) aims to assess the recognition utility of face samples and is essential for reliable face recognition (FR) systems. Existing approaches require…
ViT-FIQA: Assessing Face Image Quality using Vision Transformers
Andrea Atzori, Fadi Boutros, Naser Damer
Face Image Quality Assessment (FIQA) aims to predict the utility of a face image for face recognition (FR) systems. State-of-the-art FIQA methods mainly rely on convolutional neura…
Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +56
Synthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including…
The Impact of Balancing Real and Synthetic Data on Accuracy and Fairness in Face Recognition
Andrea Atzori, Pietro Cosseddu, Gianni Fenu +1
Over the recent years, the advancements in deep face recognition have fueled an increasing demand for large and diverse datasets. Nevertheless, the authentic data acquired to creat…
If It's Not Enough, Make It So: Reducing Authentic Data Demand in Face Recognition through Synthetic Faces
Andrea Atzori, Fadi Boutros, Naser Damer +2
Recent advances in deep face recognition have spurred a growing demand for large, diverse, and manually annotated face datasets. Acquiring authentic, high-quality data for face rec…
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +55
Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class v…
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…
(Un)fair Exposure in Deep Face Rankings at a Distance
Andrea Atzori, Gianni Fenu, Mirko Marras
Law enforcement regularly faces the challenge of ranking suspects from their facial images. Deep face models aid this process but frequently introduce biases that disproportionatel…
The More Secure, The Less Equally Usable: Gender and Ethnicity (Un)fairness of Deep Face Recognition along Security Thresholds
Andrea Atzori, Gianni Fenu, Mirko Marras
Face biometrics are playing a key role in making modern smart city applications more secure and usable. Commonly, the recognition threshold of a face recognition system is adjusted…
Explaining Bias in Deep Face Recognition via Image Characteristics
Andrea Atzori, Gianni Fenu, Mirko Marras
In this paper, we propose a novel explanatory framework aimed to provide a better understanding of how face recognition models perform as the underlying data characteristics (prote…
Heimdall: an AI-based infrastructure for traffic monitoring and anomalies detection
Andrea Atzori, Silvio Barra, Salvatore Carta +2
Since their appearance, Smart Cities have aimed at improving the daily life of people, helping to make public services smarter and more efficient. Several of these services are oft…