Face detection model training method and device

A face detection and model training technology, applied in the field of face detection, can solve the problem of low model prediction accuracy, and achieve the effect of improving detection accuracy and guaranteeing detection efficiency

Inactive Publication Date: 2019-01-25
BEIJING KUANGSHI TECH
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Problems solved by technology

However, the models used in current single-stage detection methods have low predictive accuracy

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  • Face detection model training method and device
  • Face detection model training method and device
  • Face detection model training method and device

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Embodiment Construction

[0060] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts belong to the protection scope of the present invention.

[0061] It should be noted that like numerals and let...

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Abstract

The invention relates to the technical field of face detection, and provides a face detection model training method and device. The method comprises the following steps: extracting a feature map of atraining image by using a feature extraction network and determining a training sample; taking i as 1 to M, inputting the feature map to the i-th personal face detection network, obtaining a prediction box corresponding to the training sample to obtain a position and a probability of the existence of a face in the prediction box; Calculating the loss of the i-th personal face detection network according to the classification label of the training sample; When i is less than M, determining a classification label of the training sample when calculating the loss of the (i+1)th human face detection network according to the positional relationship between the prediction frame and the real frame corresponding to the training sample; When i is M, the total loss of M personal face detection network is obtained and the parameters of face detection model are updated; Continue to train the face detection model until the end of the training conditions are met. The precision of face detection modeltrained by this method is better than that of the existing single-stage face detection model.

Description

technical field [0001] The present invention relates to the technical field of face detection, in particular to a face detection model training method and device. Background technique [0002] Face detection is the cornerstone of facial analysis algorithms, in face alignment, face modeling, face relighting, face recognition, face beauty, face AR, face verification / authentication, head pose It has applications in tasks such as expression tracking / recognition, gender / age recognition, etc. The goal of face detection is to, given any image, determine whether there is a face in the image, and if so, return the position of each face in the image, usually represented by a prediction box (upper left corner coordinates, length, width). [0003] Existing face detection methods can be roughly divided into one-stage detection and two-stage detection. Among them, the single-stage detection method can directly output the predicted frame of the face on the image, and has high detection e...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/161G06V40/168G06F18/214
Inventor 王剑锋李作新俞刚袁野
Owner BEIJING KUANGSHI TECH
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