A Face Recognition Method Using ResNet34 and RetinaFace

Abstract

A new face recognition method is proposed by utilizing ResNet34 and RetinaFace, which is based on a lightweight framework for Python named Deepface. The new method is used to improve two shortcomings in the related literature: (1) the susceptibility of face recognition to interference, and (2) the quite limited number of faces detected in an image. First, the RetinaFace detector is used to replace the common detector to get more facial feature points and expand the area for detecting faces. Thus, the number of faces detected in the same image is increased. Then, ResNet34 model is applied to replace the default model in Deepface to improve the anti-interference in face recognition. Finally, experiments demonstrate that the new method is superior to the default one.