Face image quality assessment: A literature survey

T Schlett, C Rathgeb, O Henniger, J Galbally… - ACM Computing …, 2022 - dl.acm.org
The performance of face analysis and recognition systems depends on the quality of the
acquired face data, which is influenced by numerous factors. Automatically assessing the …

Magface: A universal representation for face recognition and quality assessment

Q Meng, S Zhao, Z Huang… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
The performance of face recognition system degrades when the variability of the acquired
faces increases. Prior work alleviates this issue by either monitoring the face quality in pre …

Biometric quality: Review and application to face recognition with faceqnet

J Hernandez-Ortega, J Galbally, J Fiérrez… - arxiv preprint arxiv …, 2020 - arxiv.org
" The output of a computerised system can only be as accurate as the information entered
into it." This rather trivial statement is the basis behind one of the driving concepts in …

SER-FIQ: Unsupervised estimation of face image quality based on stochastic embedding robustness

P Terhorst, JN Kolf, N Damer… - Proceedings of the …, 2020 - openaccess.thecvf.com
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 …

SDD-FIQA: Unsupervised face image quality assessment with similarity distribution distance

FZ Ou, X Chen, R Zhang, Y Huang… - Proceedings of the …, 2021 - openaccess.thecvf.com
Abstract In recent years, Face Image Quality Assessment (FIQA) has become an
indispensable part of the face recognition system to guarantee the stability and reliability of …

CR-FIQA: face image quality assessment by learning sample relative classifiability

F Boutros, M Fang, M Klemt, B Fu… - Proceedings of the …, 2023 - openaccess.thecvf.com
Face image quality assessment (FIQA) estimates the utility of the captured image in
achieving reliable and accurate recognition performance. This work proposes a novel FIQA …

SensitiveNets: Learning agnostic representations with application to face images

A Morales, J Fierrez, R Vera-Rodriguez… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This work proposes a novel privacy-preserving neural network feature representation to
suppress the sensitive information of a learned space while maintaining the utility of the …

Few-shot adaptation of generative adversarial networks

E Robb, WS Chu, A Kumar, JB Huang - arxiv preprint arxiv:2010.11943, 2020 - arxiv.org
Generative Adversarial Networks (GANs) have shown remarkable performance in image
synthesis tasks, but typically require a large number of training samples to achieve high …

Qmagface: Simple and accurate quality-aware face recognition

P Terhörst, M Ihlefeld, M Huber… - Proceedings of the …, 2023 - openaccess.thecvf.com
In this work, we propose QMagFace, a simple and effective face recognition solution
(QMagFace) that combines a quality-aware comparison score with a recognition model …

Troubleshooting ethnic quality bias with curriculum domain adaptation for face image quality assessment

FZ Ou, B Chen, C Li, S Wang… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …