Face recognition model training and recognition method, storage medium and related equipment

A face recognition and training method technology, applied in the field of recognition, can solve problems such as inaccurate face recognition model training, and achieve the effect of ensuring training accuracy and realizing accurate recognition

Pending Publication Date: 2021-01-22
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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Problems solved by technology

For shallow data, if the aforementioned training method (traditional training metho

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  • Face recognition model training and recognition method, storage medium and related equipment
  • Face recognition model training and recognition method, storage medium and related equipment
  • Face recognition model training and recognition method, storage medium and related equipment

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[0066]In order to make the purpose, technical solutions and advantages of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the drawings in the embodiments of this application. Obviously, the described embodiments are only It is a part of the embodiments of this application, but not all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of this application. In the case of no conflict, the embodiments in the application and the features in the embodiments can be combined with each other arbitrarily. The steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described m...

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Abstract

The embodiment of the invention discloses a face recognition model training method, a face recognition model recognition method, a storage medium and related equipment. The training method comprises the steps of obtaining at least two groups of images under Nth iteration; according to the at least two groups of images, obtaining two groups of training data sets under the Nth iteration; processingthe first group of training data set by the auxiliary model under the Nth iteration to obtain a first feature group of the human face under the Nth iteration; processing the second group of training data set by the main model under the Nth iteration to obtain a second feature group of the human face under the Nth iteration; calculating a loss function value under the Nth iteration according to thefirst feature group and the second feature group; and at least determining whether to update the main model under the Nth iteration for the corresponding time according to the loss function value under the Nth iteration.

Description

technical field [0001] The present application relates to the field of recognition technology, and in particular to a face recognition model training method, a face recognition method, related equipment, and a computer-readable storage medium. Background technique [0002] The current face recognition training method based on deep learning is to let the convolutional neural network model learn the feature expression of the face on the training data set, and identify the identity information of the face to be recognized by calculating the similarity score between the face features. If the aforementioned convolutional neural network model is regarded as a face recognition model, the training method for the commonly used face recognition model in the related art is to regard face recognition as a multi-classification task, and use the convolutional neural network model The fully connected layer and the loss function calculate the probability that the face to be recognized belon...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V40/172G06V40/168G06N3/045
Inventor 石海林杜航王军梅涛
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
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