3 papers
cs.CV2026
What Makes Adversarial Examples Transfer Across Deepfake Detectors?
Rafael M. Mamede, Pedro C. Neto, Ana F. Sequeira
Deepfake detectors remain vulnerable to transfer-based black-box attacks, in which adversarial examples are generated on a source surrogate model and transferred to a target model,…
cs.CV2024
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)…
cs.CV2024
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…