The availability of large-scale authentic face databases has been crucial to the significant
advances made in face recognition research over the past decade. However, legal and …

Face recognition systems have significantly advanced in recent years, driven by the
availability of large-scale datasets. However, several issues have recently came up …

In recent years, there has been a growing interest in synthetic data for several computer
vision applications, such as automotive, detection and tracking, surveillance, medical image …

This article presents FRCSyn-onGoing, an ongoing challenge for face recognition where
researchers can easily benchmark their systems against the state of the art in an open …

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 …

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 …

Diffusion models are becoming increasingly popular in synthetic data generation and image
editing applications. However, these models can amplify existing biases and propagate …

Large-scale face recognition datasets are collected by crawling the Internet and without
individuals' consent, raising legal, ethical, and privacy concerns. With the recent advances in …

As a generalization of fuzzy sets, intuitionistic fuzzy sets (IFSs) are more capable of
representing and addressing uncertainty in real-world problems. As a result, IFSs have been …

Deep generative models have recently presented impressive results in generating realistic
face images of random synthetic identities. To generate multiple samples of a certain …