Fig. 8From: Assessment framework for deepfake detection in real-world situationsCross-manipulation experiments on FaceForensice++ (Raw) dataset with XceptionNet trained on four different types of manipulated dataset separately, namely Deepfake, Face2Face, FaceSwap, NeuralTextures. AUC (%) scores are compared between the XceptionNet model trained with or without the SDAug techniqueBack to article page