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Found 10 papers, 6 papers with code
FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment
This comparison shows that, even though FaceQgen does not surpass the best existing face quality assessment methods in terms of face recognition accuracy prediction, it achieves good enough results to demonstrate the potential of semi-supervised learning approaches for quality estimation (in particular, data-driven learning based on a single high quality image per subject), having the capacity to improve its performance in the future with adequate refinement of the model and the significant advantage over competing methods of not needing quality labels for its development.
Introduction to Presentation Attack Detection in Face Biometrics and Recent Advances
The main scope of this chapter is to serve as an introduction to face presentation attack detection, including key resources and advances in the field in the last few years.
FaceQvec: Vector Quality Assessment for Face Biometrics based on ISO Compliance
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 standard that defines general quality guidelines for face images that would make them acceptable or unacceptable for use in official documents such as passports or ID cards.
DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation
This work introduces a novel DeepFake detection framework based on physiological measurement.
Biometric Quality: Review and Application to Face Recognition with FaceQnet
After a gentle introduction to the general topic of biometric quality and a review of past efforts in face quality metrics, in the present work, we address the need for better face quality metrics by developing FaceQnet.
Heart Rate Estimation from Face Videos for Student Assessment: Experiments on edBB
In this study we estimate the heart rate from face videos for student assessment.
A Comparative Evaluation of Heart Rate Estimation Methods using Face Videos
This paper presents a comparative evaluation of methods for remote heart rate estimation using face videos, i. e., given a video sequence of the face as input, methods to process it to obtain a robust estimation of the subjects heart rate at each moment.
edBB: Biometrics and Behavior for Assessing Remote Education
We present a platform for student monitoring in remote education consisting of a collection of sensors and software that capture biometric and behavioral data.
Quality-based Pulse Estimation from NIR Face Video with Application to Driver Monitoring
In this paper we develop a robust for heart rate (HR) estimation method using face video for challenging scenarios with high variability sources such as head movement, illumination changes, vibration, blur, etc.
FaceQnet: Quality Assessment for Face Recognition based on Deep Learning
Several conclusions can be drawn from this work, most notably: 1) we managed to employ an existing ICAO compliance framework and a pretrained CNN to automatically label data with quality information, 2) we trained FaceQnet for quality estimation by fine-tuning a pre-trained face recognition network (ResNet-50), and 3) we have shown that the predictions from FaceQnet are highly correlated with the face recognition accuracy of a state-of-the-art commercial system not used during development.
