False face video identification method and system and readable storage medium

A video and video frame technology, applied in the field of computer vision and artificial intelligence, can solve the problems of high time and equipment cost, low efficiency of fake images, and further improvement of the accuracy of identifying deep face forgery videos, etc., so as to reduce time cost, The effect of good discrimination

Pending Publication Date: 2020-11-20
GUANGDONG UNIV OF TECH
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Problems solved by technology

However, this method has its disadvantages. It uses artificial intelligence-based synthesis algorithms to generate fake images with l...

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  • False face video identification method and system and readable storage medium
  • False face video identification method and system and readable storage medium
  • False face video identification method and system and readable storage medium

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Embodiment Construction

[0059] In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0060] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described here. Therefore, the protection scope of the present invention is not limited by the specific details disclosed below. EXAMPLE LIMITATIONS.

[0061] figure 1 A flow chart of a fake human face video identification method based on a convolutional neural network and an attention mechanism of the present invention is shown.

[0062] Such as ...

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Abstract

The invention discloses a false face video identification method and system based on a convolutional neural network and an attention mechanism, and a readable storage medium. The method comprises thesteps: carrying out the sampling of an inputted video sequence, and obtaining N video frames; detecting, cutting and aligning the video frame to a human face to obtain a high-quality human face image,and obtaining a to-be-detected sample set; inputting the to-be-tested sample set into a trained deep convolutional neural network model of an attention mechanism to obtain an output result which is aresult of judging the authenticity of the video. According to the method disclosed in the invention, the negative sample is obtained through the special processing method of the positive sample, thetime cost of obtaining the negative sample is reduced, the face image of the fake face video is simulated well, and the trained network has good identification capability; in addition, the method canhighlight the manipulated image regions, thereby guiding the neural network to detect the regions, facilitating the detection of face counterfeiting, and improving the accuracy of an original CNN model.

Description

technical field [0001] The invention relates to the fields of computer vision and artificial intelligence, in particular to a method, system and readable storage medium for discriminating fake face videos based on a convolutional neural network and an attention mechanism. Background technique [0002] With the maturity of the application of deep learning technology, deepfake videos based on deepfake are becoming more and more popular. This deep-learning technique can create face-swapping videos that look like real ones. These fake videos look very realistic. So far, not only have these videos been faked in the context of pornography and verbal attacks to make people think that some celebrities are doing something discreditable to them, but even more egregiously, deepfake videos have also been used to impersonate political figures speech. U.S. Democratic Congressman Adam Schiff even warned that videos generated by Deepfake could have a disastrous impact on the 2020 U.S. el...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/172G06V40/168G06N3/048G06N3/045G06F18/241
Inventor 方俊涛孙宇平凌捷罗玉
Owner GUANGDONG UNIV OF TECH
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