212 citations · 436 across the 99 of their papers we have counts for
13 papers · 2 filters
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…
FRoundation: Are Foundation Models Ready for Face Recognition?
Tahar Chettaoui, Naser Damer, Fadi Boutros
Foundation models are predominantly trained in an unsupervised or self-supervised manner on highly diverse and large-scale datasets, making them broadly applicable to various downs…
First Competition on Presentation Attack Detection on ID Card
Juan E. Tapia, Naser Damer, Christoph Busch +12
This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB2024). The compet…
A Survey on Drowsiness Detection -- Modern Applications and Methods
Biying Fu, Fadi Boutros, Chin-Teng Lin +1
Drowsiness detection holds paramount importance in ensuring safety in workplaces or behind the wheel, enhancing productivity, and healthcare across diverse domains. Therefore accur…
Beyond Spatial Explanations: Explainable Face Recognition in the Frequency Domain
Marco Huber, Naser Damer
The need for more transparent face recognition (FR), along with other visual-based decision-making systems has recently attracted more attention in research, society, and industry.…
AdaDistill: Adaptive Knowledge Distillation for Deep Face Recognition
Fadi Boutros, Vitomir Štruc, Naser Damer
Knowledge distillation (KD) aims at improving the performance of a compact student model by distilling the knowledge from a high-performing teacher model. In this paper, we present…
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…
GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes
Jan Niklas Kolf, Naser Damer, Fadi Boutros
Face Image Quality Assessment (FIQA) estimates the utility of face images for automated face recognition (FR) systems. We propose in this work a novel approach to assess the qualit…
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…
AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation
Žiga Babnik, Fadi Boutros, Naser Damer +2
Face Image Quality Assessment (FIQA) techniques have seen steady improvements over recent years, but their performance still deteriorates if the input face samples are not properly…
SDFR: Synthetic Data for Face Recognition Competition
Hatef Otroshi Shahreza, Christophe Ecabert, Anjith George +25
Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advance…
IEEE BigData 2023 Keystroke Verification Challenge (KVC)
Giuseppe Stragapede, Ruben Vera-Rodriguez, Ruben Tolosana +26
This paper describes the results of the IEEE BigData 2023 Keystroke Verification Challenge (KVC), that considers the biometric verification performance of Keystroke Dynamics (KD),…
Model Compression Techniques in Biometrics Applications: A Survey
Eduarda Caldeira, Pedro C. Neto, Marco Huber +2
The development of deep learning algorithms has extensively empowered humanity's task automatization capacity. However, the huge improvement in the performance of these models is h…