Modern face recognition (FR) models excel in constrained scenarios, but often suffer from
decreased performance when deployed in unconstrained (real-world) environments due to …

Abstract Face Image Quality Assessment (FIQA) is pivotal for guaranteeing the accuracy of
face recognition in unconstrained environments. Recent progress in deep quality-fitting …

Face inpainting is a challenging task aiming to fill the damaged or masked regions in face
images with plausibly synthesized contents. Based on the given information, the …

In this paper we develop FaceQvec, a software component for estimating the conformity of
facial images with each of the points contemplated in the ISO/IEC 19794-5, a quality …

State-of-the-art Face Recognition (FR) models perform well in constrained scenarios, but
frequently fail in difficult real-world scenarios, when no quality guarantees can be made for …

Face frontalization is a process of synthesizing a realistic and identity-preserving face view
from different face pose images. It is an essential preprocessing step for face recognition. As …

Recent advances in facial recognition technology have achieved outstanding performance,
but unconstrained face recognition remains an ongoing issue. Facial-image-quality …

Face frontalization is the process of synthesizing realistic and identity-preserving frontal
views from face images in different poses and is an essential preprocessing step for face …

Modern face recognition (FR) models excel in constrained scenarios, but often suffer from
decreased performance when deployed in unconstrained (real-world) environments due to …

The correctness of the generated face data, which is impacted by a number of variables,
significantly affects how well face analysis and recognition systems perform. By …