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 …

Abstract Face Image Quality Assessment (FIQA) lays the foundation for ensuring the stability
and accuracy of face recognition systems. However, existing FIQA methods mainly formulate …

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 …

Although face recognition has made impressive progress in recent years, we ignore the
racial bias of the recognition system when we pursue a high level of accuracy. Previous …

Large Language Models (LLMs) such as GPT developed by OpenAI, have already shown
astonishing results, introducing quick changes in our society. This has been intensified by …

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 …

Abstract Privacy-Preserving Action Recognition (PPAR) aims to transform raw videos into
anonymous ones to prevent privacy leakage while maintaining action clues, which is an …

Abstract We introduce Semi-supervised Performance Evaluation for Face Recognition (SPE-
FR). SPE-FR is a statistical method for evaluating the performance and algorithmic bias of …

The progress of brain cognition and learning mechanisms has provided new inspiration for
the next generation of artificial intelligence (AI) and provided the biological basis for the …