Face recognition (FR) systems have a growing effect on critical decision-making processes.
Recent works have shown that FR solutions show strong performance differences based on …

Face image quality is an important factor to enable high-performance face recognition
systems. Face quality assessment aims at estimating the suitability of a face image for the …

Synthetic data is emerging as a substitute for authentic data to solve ethical and legal
challenges in handling authentic face data. The current models can create real-looking face …

Soft-biometrics play an important role in face biometrics and related fields since these might
lead to biased performances, threaten the user's privacy, or are valuable for commercial …

Deeply-learned face representations enable the success of current face recognition
systems. Despite the ability of these representations to encode the identity of an individual …

Face biometrics play a primary role in smart cities, from consumer-to organizational-level
applications. This class of technologies has been recently shown to emphasize performance …

Current face recognition systems achieve high progress on several benchmark tests.
Despite this progress, recent works showed that these systems are strongly biased against …

Transfer learning is a popular method for tuning pretrained (upstream) models for different
downstream tasks using limited data and computational resources. We study how an …

In recent years, image and video manipulations with Deepfake have become a severe
concern for security and society. Many detection models and datasets have been proposed …

The success of modern face recognition systems is based on the advances of deeply-
learned features. These embeddings aim to encode the identity of an individual such that …