AI face-changing video detection method based on multi-task learning model

Abstract

The invention relates to an AI face-changing video detection method based on a multi-task learning model, which belongs to the field of computer vision and deep learning, and comprises the following steps: pre-training a model based on multi-task learning to detect a modified face-changing video, and positioning a modified area for each query, the model is an automatic encoder and comprises a Y-shaped automatic decoder. A semi-supervised learning method is used for improving the generality of the network, valuable information is shared before multiple tasks, the sum of an activation loss function, a segmentation loss function and a reconstruction loss function is reduced, and an optimizer is used for optimization, so that the performance is improved. And for video input detection, averaging is performed on the probabilities of all frames to obtain the probability that the input is true or false. According to the method, AI face-changing video detection can be improved.

Description

technical field [0001] The invention belongs to the field of computer vision and deep learning, and in particular relates to a false video detection method based on computer and deep learning algorithms, which is used to quickly and accurately determine falsely generated video files and locate video tampered parts. Background technique [0002] With the development of deep learning, there are more and more AI face-changing technologies, the technology is becoming more and more mature, and the effect of AI face-changing is getting better and better. With the development of AI face-changing technology, it has also brought many negative impact. For example, many people with malicious intentions use these technologies to change the faces of celebrities to pornographic pictures and videos, or change the faces of some politicians to videos with bad remarks shot by criminals, trying to shake the world Relationships, such as speeches by the President of the United States, the Presi...

AI Technical Summary

Problems solved by technology

[0003] In the current public AI face-changing video detection, it is only detected from a single feature, such as based on blinking, mouth shape, and skin edge, resulting in poor detection performance

In the calculation process, most detection methods consider the entire image for calculation, which greatly increases the calculation cost, so that it cannot detect face-changing videos efficiently and accurately.

[0004] The present invention mainly proposes a multi-task learning model to solve the problem that AI face-changing video detection cannot be efficient and accurate

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