Age estimation method and device and training method and device of age estimation model

Abstract

The invention provides an age estimation method, an age estimation model training method and an age estimation model training device. The age estimation method comprises the following steps: acquiringa to-be-processed image containing a target object; inputting the to-be-processed image into a pre-trained age estimation model; outputting an age classification result corresponding to the to-be-processed image through a classification network of the age estimation model, and outputting an age regression result corresponding to the to-be-processed image through a regression network of the age estimation model; and determining the age of the target object based on the age classification result and the age regression result. According to the method, when the age of the target object is estimated through the age estimation model, the to-be-processed image can be classified to obtain the age classification result, the to-be-processed image is subjected to regression processing to obtain theage regression result, and the age of the target object is determined according to the age classification result and the age regression result. The classification and regression integrated mode improves the precision of age estimation.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an age estimation method, a training method and a device for an age estimation model. Background technique [0002] As an important face attribute, age has a wide range of applications in the fields of human-computer interaction, intelligent business, security monitoring and entertainment. In related technologies, the age of the person in the image can be estimated by a trained deep learning model; during the training process of the deep learning model, the age estimation task is regarded as a classification task or a regression task, and the loss value of the age estimation is calculated, and then The deep learning model is trained based on the loss value. In this way, the data referenced by the deep learning model during the training process is limited, which limits the accuracy of the model's estimated age. Contents of the invention [0003] In view of this...

AI Technical Summary

Problems solved by technology

In related technologies, the age of the person in the image can be estimated by a trained deep learning model; during the training process of the deep learning model, the age estimation task is regarded as a classification task or a regression task, and the loss value of the age estimation is calculated, and then The deep learning model is trained based on the loss value. In this method, the data referenced by the deep learning model during the training process is limited, which limits the accuracy of the model's estimated age.

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