A face image synthesis method and device based on adversarial learning

A face image and image technology, applied in the field of computer vision, can solve problems such as changes in the face angle of view and cannot solve the problem of occlusion, and achieve the effect of excellent performance

Active Publication Date: 2019-05-28
CHINA NAT ELECTRONICS IMP & EXP CORP
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AI Technical Summary

Problems solved by technology

TP-GAN can only solve the problem of changing the perspective of the face, and cannot solve the problem of occlusion

Method used

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  • A face image synthesis method and device based on adversarial learning
  • A face image synthesis method and device based on adversarial learning
  • A face image synthesis method and device based on adversarial learning

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Embodiment Construction

[0042] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below through specific embodiments and accompanying drawings.

[0043] This embodiment provides a face synthesis method based on adversarial learning. The overall process of the method and the network structure adopted are as follows: figure 1 shown, including the following steps:

[0044] S1: Crop the face image in the Multi-PIE database according to the detected face key points.

[0045] S2: Select 24 objects from the Caltech 101, Caltech 256 and Cambridge Hand Gesture datasets. For the face image, use random noise or the above-mentioned objects to randomly block 1 / 4 of the face image.

[0046] S3: Use the Helen database to train the face semantic segmentation network. The human face semantic segmentation network designed in the present invention includes an encoder and a decoder. There are five convolu...

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Abstract

The invention relates to a face image synthesis method and device based on adversarial learning. The method provides a novel generative adversarial network (FC-GAN), and aims to synthesize a front face image under the standard illumination from an occluded face image. The FC-GAN uses a convolutional neural network structure an encoder-decoder as a generator, and two discriminators are introduced at the same time, one is a global discriminator used for distinguishing the authenticity of a whole face image, and meanwhile, the identity information of a person is kept unchanged; and the other oneis a local discriminator which is used for distinguishing the authenticity of the shielding area in the human face. In addition, a human face semantic segmentation network is introduced to strengthenthe consistency of five sense organs of a human face in the generated image. And by comparing the semantic tags of the synthesized face image and the real face image, the gradient is transmitted backto the generator to adjust the five sense organs of the synthesized face image. Experimental results on the reference data set Multi-PIE show that the FC-GAN performance is superior to that of most existing methods.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a face image synthesis method and device based on adversarial learning. Background technique [0002] Face recognition is an important research topic in the field of computer vision. Due to its ease of use, high accuracy, and non-intrusive features, it has shown great application potential in many fields such as security monitoring, financial services, mobile terminals, and physical businesses. In the past ten years, deep learning has achieved great success in face recognition, and the performance of face recognition systems based on deep neural networks has significantly exceeded that of face recognition systems based on manually designed features. Many start-up companies researching face recognition technology have sprung up like mushrooms after rain, such as Shangtang Technology, Megvii Technology, Cloudwalk Technology and Yitu Technology. [0003] The pe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 张婷张招亮唐文杰廖欢梁雅萌李慧
Owner CHINA NAT ELECTRONICS IMP & EXP CORP
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