Super-division model training and face recognition method and device, medium and electronic equipment

A face recognition and training method technology, applied in the field of face recognition, can solve the problem of low-quality face image recognition efficiency and other problems, and achieve the effect of high accuracy and clear image

Pending Publication Date: 2021-07-30
杭州网易智企科技有限公司
View PDF10 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present disclosure is to provide a super-resolution model training method, a super-resolution model training device, a

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Super-division model training and face recognition method and device, medium and electronic equipment
  • Super-division model training and face recognition method and device, medium and electronic equipment
  • Super-division model training and face recognition method and device, medium and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific deta...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to the field of face recognition, in particular to a super-division model training and face recognition method and device, a computer readable storage medium and electronic equipment, and the method comprises the steps of obtaining a first high-quality face image sample and a corresponding low-quality face image sample, performing super-resolution reconstruction processing on the low-quality face image sample by the to-be-trained model to generate a corresponding target high-quality face image, and obtaining a first loss function of the to-be-trained model; obtaining identity information, obtaining a second high-quality face image sample corresponding to the identity information, and constructing an image multi-component system; extracting a plurality of face features of a plurality of face images in the face image multi-tuple and calculating a second loss function of the to-be-trained model; and iteratively updating neural network parameters of the to-be-trained model through the first loss function and the second loss function so as to train the super-division model. Through the technical scheme of the embodiment of the invention, the problem of relatively low recognition efficiency of a low-quality face image can be solved.

Description

technical field [0001] The present disclosure relates to the technical field of face recognition, and in particular, to a super-resolution model training method, a face recognition method, a super-resolution model training device, a face recognition device, a computer-readable storage medium, and electronic equipment. Background technique [0002] Face recognition is a biometric technology for identification based on human facial feature information. With the development of software and hardware, deep learning has been more and more widely used in the field of face recognition. Face recognition can detect and track faces in images according to computers, quickly identify specific people, and make respond accordingly. [0003] In the prior art, a video camera or camera is usually used to collect images or video streams containing human faces, and to track the images, and then perform facial recognition on detected human faces. [0004] However, in some application scenarios...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06N3/08G06N3/04G06T3/40G06K9/00
CPCG06N3/084G06N3/04G06T3/4053G06T2207/30168G06T2207/30201G06V40/168
Inventor 徐国智朱浩齐李雨珂孙景润杨卫强
Owner 杭州网易智企科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products