Table 6.

Comparative analysis with existing methods using various DF datasets.

Study	Method	Dataset	Performance (AC)
E.D. Cannas [50]	Group of CNN	FF++(c23)	84%
Sabir [24]	CNN + GRU + STN	FF++, DF	96.9%
		FF++, F2F	94.35%
		FF++,FS	96.3%
J.C. Neves [51]	3D head poses	UADFV	97%
F. Juang	Eyeblink + LRCN	Self-made dataset	97.5%
Ciftci [52]	Biological signals	Self-made deep fakes dataset	91.07%
Tarasiou [53]	A lightweight architecture	DFDC	78.76%
Keramatfar [54]	Multi-threading using Learning with Attention	Celeb-DF	70.2%
Nirkin [55]	FACE X-RAY	Celeb-DF	81.58%
Ciftci [52]	Bio Identification	Celeb-DF	90.50%
Proposed Method		FF++, FS	99.13%
		FF++,F2F	98.08%
		FF++,NT	99.09%