da/sec scientific talk on Biometrics

Topic: Deep Generative Networks in Face Recognition with Application to Face Image Quality Assessment

by Marcel Grimmer
D19/2.03a, December 19, 2024 (Thursday), 12.00 noon

Keywords — Biometrics, Generative AI, Quality Assessment

Abstract

„The widespread adoption of face recognition systems for authentication spans from convenience-based applications (e.g., smartphone unlocking) to security-critical applications (e.g., border control). This trend stems from the transition from traditional machine learning to deep learning-based recognition models, which have significantly improved recognition accuracy and robustness against various sources of variation. However, the effectiveness of deep neural networks largely depends on the availability of sufficient training and evaluation data. One possible solution to meet the high demand for data is to exploit recent advances in deep generative models, which can generate highly realistic facial images that are indistinguishable from images upon human inspection. Therefore, this presentation outlines how large-scale data collection can be circumvented by using deep generative models for evaluating face recognition systems and deriving quality assessment measures.“