FaceNet face recognition algorithm is currently the mainstream face recognition algorithm,its fast running speed is widely used in the industry.FaceNet face recognition network has the problem of low accuracy in face occlusion face recognition.This paper presents a FaceNet face recognition algorithm that combines attention mechanism.Based on FaceNet,GhostNet feature extraction network is introduced to extract face features better.Feature pyramid networks (FPN)is combined to enhance feature extraction network to enlarge local information in three scale feature maps, enhance feature extraction under different perception fields and enhance more important feature information.The experimental results show that the face recognition algorithm in this paper achieves good recognition results,and the accuracy reaches 99.62%in the face dataset(LWF).Better detection results are also obtained for face recognition with occlusion,which can accurately identify face targets with occlusion.