Face Recognition Security Enhancement Using DeepFake and FaceNet

Abstract: Convolutional Neural Networks (CNNs) have been very successful in extracting meaningful features from face images and attaining remarkable performance in face recognition tasks, but there are still challenges that impacttheaccuracyandrobustnessoffacerecognitionsystems,includingvariationsinlightingconditions,facial expressions, occlusions, and aging. This article discusses the usage of CNNs for face recognition, presents the state-of-the-art CNN architectures used in this application, and also addresses important factors including data preprocessing, networkoptimization,andreal-timeprocessing.WeevaluatedifferentCNN-basedmodelsforface recognition and compare their performance under various real-world scenarios