FaceQnet: Quality Assessment for Face Recognition based on Deep Learning

6 code implementations • 3 Apr 2019 • Javier Hernandez-Ortega, Javier Galbally, Julian Fierrez, Rudolf Haraksim, Laurent Beslay

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.

Face Recognition