Synthesis and Recognition of Internet Celebrity Face Based on Deep Learning

Abstract

The similarity among Internet Celebrity Faces brings a big challenge to the recognition and verification of faces. To study this problem, more than 20,000 Internet Celebrity Face pictures are collected from the Internet. We utilize these faces to train the Variational Auto-Encoder (VAE) to synthesize the fake Internet Celebrity Faces and compare the faces with real samples. Results show that the performance of the deep network in Internet Celebrity Face greatly decreases. 20 pairs of the same or different Internet Celebrity Faces are selected to test the human’s ability to recognize Internet Celebrity Faces by questionnaire. The comparison with the VGG deep network shows that the deep learning algorithm performs much better than human in terms of recognition accuracy.