A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks

Abstract

The device group based on the Internet of Things (IoT) has been used in face recognition in real life, so it is more necessary to discuss the current data security issues and social hot issues. The Internet of Things device combines edge conditions and many recognizers to generative adversarial networks. On the premise of meeting the needs of partial occlusion of users, face recovery is completed through information reorganization. CelebA training set is used to simulate face occlusion, and the model is trained and tested. The results show that the method can recover the complete image of the protection for the facial privacy of specific people. At the same time, the IoT device using this method ensures that the face information is not easy to have tampered with when attacked.