人脸年龄标签在跨衰老人脸识别中的使用

In recent years, with the development of deep learning, face recognition has achieved good results, and has a mature and stable application market. However, the problem of cross-age face recognition is still waiting for solution. Cross-age databases need to contain pictures of the same person at different ages, which has led to the scarcity of large age databases available today. Therefore, we propose two methods to make full use of the existing age database labels. Firstly, aiming at the use of age labels in network structure, we propose an age embeeding method to eliminateage information from deep features.In this method, the image age labels are transformed into age vectors after processing, then they are cascaded with deep features before classified.Secondly, in order to include age in loss function, we design a new loss function, which makes the weights of images (too old or too young) larger. In this method,age label is converted into age weight and then multiplied with the center loss of the image to obtain a new loss.