Assessment framework for deepfake detection in real-world situations

EURASIP Journal on Image and Video Processing

Table 5 AUC (%) scores of three selected deepfake detection methods trained with the SDAug augmentation method on the distorted variants of the FFpp test set

Methods	TrainSet	Compression		Brightness		Grayscale	Contrast	Flipping		Resolution		Gaussian Noise	Vintage Filter	Overall Average
		C23	C40	Increase	Decrease			Horizontal	Vertical	x2	x4
CapsuleNet	FFpp- Raw	77.97	54.14	73.31	70.62	68.38	69.31	73.13	63.20	65.43	56.99	54.14	72.94	66.63
+SDAug		92.76	72.32	89.56	89.50	88.17	89.93	89.40	62.61	78.55	74.93	81.86	85.21	82.90
XceptionNet		69.49	55.70	65.92	66.40	65.51	65.32	65.26	57.36	57.23	55.90	50.50	66.90	61.79
+SDAug		94.89	80.53	93.36	93.05	92.64	92.98	92.32	57.65	88.42	81.60	88.91	90.47	87.24
SBIs		90.43	76.27	86.38	86.47	86.27	85.94	85.98	79.28	76.35	63.62	71.52	86.54	81.25
+SDAug		89.31	76.60	85.55	86.24	85.41	84.76	85.48	78.67	77.06	64.31	77.13	86.11	81.39