Face forgery detection method and system based on graph convolutional neural network

Abstract

The present application proposes a face forgery detection method based on a graph convolutional neural network, which includes: obtaining a to-be-detected face video; inputting the to-be-detected face video into a trained detection model to obtain a judgment result on whether the video is forged; wherein the detection model includes: an encoder, for generating features of each frame of the to-be-detected face video; a spatiotemporal composite graph construction module, for constructing a spatiotemporal composite graph composed of the spatial graph and the temporal graph based on the features of each frame of the input video; a spatiotemporal composite graph convolution module, for performing feature learning based on the spatiotemporal composite graph to obtain classification features; and a classifier, for predicting an authenticity result of the to-be-detected face video based on the classification features.

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