Model training method and device, face recognition method and device, equipment and storage medium

Abstract

The invention discloses a model training method. The method comprises the steps that training batch data is acquired, the training batch data comprises a plurality of training samples, for each training sample, identity features and age features corresponding to sample images are acquired through a feature extraction module, and typical correlation mapping variables corresponding to the features are acquired through a typical correlation mapping module; based on the typical correlation mapping variables corresponding to the training samples, counting correlation coefficients corresponding to the training batch data through a batch correlation coefficient measurement module; performing joint supervised learning through an identity discriminator and an age discriminator, performing decorrelation training of identity features and age features through correlation coefficients, and performing training to obtain a feature extraction module meeting a training target. And based on the decorrelation-based adversarial learning, the correlation between the identity features identified by the feature extraction module and the age features is extremely low, so that the identification precisionis improved. The invention further discloses a cross-age face recognition method, a corresponding device, equipment and a medium.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular to a model training method, a cross-age face recognition method, device, equipment and storage medium. Background technique [0002] At this stage, the problem of cross-age face recognition is one of the major challenges in the field of face recognition. Age changes make face images more complex and diverse, which greatly increases the difficulty of face recognition. Cross-age face recognition technology Still in the exploratory stage. [0003] The existing cross-age face recognition mainly adopts a discriminative scheme, which is mainly based on multi-task learning of identity discrimination and age discrimination. However, since identity features and age features usually have a certain degree of correlation, so, Identity features will include some age information, making face recognition results unreliable. [0004] Therefore, how to improve the per...

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Problems solved by technology

[0002]At this stage, the problem of cross-age face recognition is one of the major challenges in the field of face recognition. Age changes make face images more complex and diverse, which is extremely Greatly increased the difficulty of face recognition, cross-age face recognition technology is still in the exploratory stage

[0003]The existing cross-age face recognition mainly adopts the discriminative scheme, which is mainly based on multi-task learning of identity discrimination and age discrimination. However, due to identity Characteristics and age characteristics usually have a certain degree of correlation, so identity characteristics will include some age information, making face recognition results unreliable

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