58 citations · 112 across the 19 of their papers we have counts for
21 papers
Balancing Beyond Discrete Categories: Continuous Demographic Labels for Fair Face Recognition
Pedro C. Neto, Naser Damer, Jaime S. Cardoso +1
Bias has been a constant in face recognition models. Over the years, researchers have looked at it from both the model and the data point of view. However, their approach to mitiga…
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…
How Knowledge Distillation Mitigates the Synthetic Gap in Fair Face Recognition
Pedro C. Neto, Ivona Colakovic, Sašo Karakatič +1
Leveraging the capabilities of Knowledge Distillation (KD) strategies, we devise a strategy to fight the recent retraction of face recognition datasets. Given a pretrained Teacher…
MST-KD: Multiple Specialized Teachers Knowledge Distillation for Fair Face Recognition
Eduarda Caldeira, Jaime S. Cardoso, Ana F. Sequeira +1
As in school, one teacher to cover all subjects is insufficient to distill equally robust information to a student. Hence, each subject is taught by a highly specialised teacher. F…
Fairness Under Cover: Evaluating the Impact of Occlusions on Demographic Bias in Facial Recognition
Rafael M. Mamede, Pedro C. Neto, Ana F. Sequeira
This study investigates the effects of occlusions on the fairness of face recognition systems, particularly focusing on demographic biases. Using the Racial Faces in the Wild (RFW)…
Massively Annotated Datasets for Assessment of Synthetic and Real Data in Face Recognition
Pedro C. Neto, Rafael M. Mamede, Carolina Albuquerque +2
Face recognition applications have grown in parallel with the size of datasets, complexity of deep learning models and computational power. However, while deep learning models evol…
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…
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…
Compressed Models Decompress Race Biases: What Quantized Models Forget for Fair Face Recognition
Pedro C. Neto, Eduarda Caldeira, Jaime S. Cardoso +1
With the ever-growing complexity of deep learning models for face recognition, it becomes hard to deploy these systems in real life. Researchers have two options: 1) use smaller mo…
Unveiling the Two-Faced Truth: Disentangling Morphed Identities for Face Morphing Detection
Eduarda Caldeira, Pedro C. Neto, Tiago Gonçalves +3
Morphing attacks keep threatening biometric systems, especially face recognition systems. Over time they have become simpler to perform and more realistic, as such, the usage of de…
An interpretable machine learning system for colorectal cancer diagnosis from pathology slides
Pedro C. Neto, Diana Montezuma, Sara P. Oliveira +10
Considering the profound transformation affecting pathology practice, we aimed to develop a scalable artificial intelligence (AI) system to diagnose colorectal cancer from whole-sl…
PIC-Score: Probabilistic Interpretable Comparison Score for Optimal Matching Confidence in Single- and Multi-Biometric (Face) Recognition
Pedro C. Neto, Ana F. Sequeira, Jaime S. Cardoso +1
In the context of biometrics, matching confidence refers to the confidence that a given matching decision is correct. Since many biometric systems operate in critical decision-maki…
OrthoMAD: Morphing Attack Detection Through Orthogonal Identity Disentanglement
Pedro C. Neto, Tiago Gonçalves, Marco Huber +3
Morphing attacks are one of the many threats that are constantly affecting deep face recognition systems. It consists of selecting two faces from different individuals and fusing t…
SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data
Marco Huber, Fadi Boutros, Anh Thi Luu +16
This paper presents a summary of the Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data (SYN-MAD) held at the 2022 International Joint Con…
OCFR 2022: Competition on Occluded Face Recognition From Synthetically Generated Structure-Aware Occlusions
Pedro C. Neto, Fadi Boutros, Joao Ribeiro Pinto +12
This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022). OCFR-2022 a…
Causality-Inspired Taxonomy for Explainable Artificial Intelligence
Pedro C. Neto, Tiago Gonçalves, João Ribeiro Pinto +4
As two sides of the same coin, causality and explainable artificial intelligence (xAI) were initially proposed and developed with different goals. However, the latter can only be c…
Myope Models -- Are face presentation attack detection models short-sighted?
Pedro C. Neto, Ana F. Sequeira, Jaime S. Cardoso
Presentation attacks are recurrent threats to biometric systems, where impostors attempt to bypass these systems. Humans often use background information as contextual cues for the…
FocusFace: Multi-task Contrastive Learning for Masked Face Recognition
Pedro C. Neto, Fadi Boutros, João Ribeiro Pinto +3
SARS-CoV-2 has presented direct and indirect challenges to the scientific community. One of the most prominent indirect challenges advents from the mandatory use of face masks in a…
My Eyes Are Up Here: Promoting Focus on Uncovered Regions in Masked Face Recognition
Pedro C. Neto, Fadi Boutros, João Ribeiro Pinto +4
The recent Covid-19 pandemic and the fact that wearing masks in public is now mandatory in several countries, created challenges in the use of face recognition systems (FRS). In th…
MFR 2021: Masked Face Recognition Competition
Fadi Boutros, Naser Damer, Jan Niklas Kolf +32
This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within the 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attra…
Deep Learning Based Analysis of Prostate Cancer from MP-MRI
Pedro C. Neto
The diagnosis of prostate cancer faces a problem with overdiagnosis that leads to damaging side effects due to unnecessary treatment. Research has shown that the use of multi-param…