Deepfake detection method based on video frame sequence prediction
A technology of forgery detection and video frame, which is applied in the direction of instruments, computing, character and pattern recognition, etc., can solve the problems of poor promotion, performance loss, and abnormal characteristics of modeling timing, so as to improve the generalization effect and increase attention , the effect of good generalization performance
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[0038] This embodiment is a depth of forgery detection method based on a video frame sequential prediction, includes the following steps of: video input trained suspicious timing model, wherein the suspicious extracted video by timing model, the input feature classifier genuine, the suspect true and false classifier output video probability of true and false.
[0039] Training time series model in the present embodiment, comprising:
[0040] Sl, the video frame by video frame sequence to disrupt module input video segment random disrupted, for video input, video random in four successive image, and then disrupted using random manner a 12 kinds of candidate disrupt species (including the case unscrambled), video frame sequence.
[0041] For a normal video frame sequence, the present embodiment randomly selected from one of 12 kinds of pre-defined manner disrupted, 12 corresponding to the tag disrupt embodiment 0-11 of the data as an additional tag, a secondary task classification t...
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