Face aging image synthesis method based on cyclic conditional generative adversarial network

Abstract

The invention discloses a face aging image synthesis method based on a cyclic conditional generative adversarial network, and belongs to the field of computer vision. The method comprises the steps offirstly selecting a generative adversarial network as a basic framework; meanwhile, taking the idea of dual learning of the cyclic generative adversarial network as reference; utilizing a supervisedlearning thought of an auxiliary discriminator; introducing a category label innovatively when the cyclic generative adversarial network is used for generating an aging picture; according to the method, the network is enabled to increase attention to specific age characteristics, an auxiliary classification branch is added to the discriminator so that the generation network is enabled to effectively utilize label information to learn specific knowledge, and generation and conversion of the generation network in images of different age groups can be completed through single training via the idea of dual learning. Through the method, the advantages of dual learning and auxiliary classification supervision thought are fully utilized, and the efficiency and picture quality of the cyclic generative adversarial network in senescence image generation are greatly improved.

Description

technical field [0001] The invention belongs to the field of computer vision, and mainly relates to the problem of synthesizing human face aging images. It is mainly used in the detection of criminal cases and the film and television entertainment industry. Background technique [0002] Face aging image synthesis is the use of computer vision related technologies to synthesize corresponding images of specified face images in different age groups on the basis of retaining the identity characteristics of the original face image. With the continuous breakthroughs in relevant theoretical research and the rapid development of the information technology industry, the research on face aging image synthesis is very extensive in public security criminal investigation, cross-aging face recognition, face data translation, and face data set expansion. Applications. In recent years, face aging image synthesis has been further developed based on the development of machine learning and d...

AI Technical Summary

Problems solved by technology

The present invention aims to overcome the existing problems in the synthetic process between the aging image and the input image, such as the inability to maintain identity consistency, the lack of individualization of the aging method of the aging image, the inaccurate age information of the aging image, and the poor quality of the aging image generation.

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