Deepfake Detection On Fakeavceleb 1

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AP

ROC AUC

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

			Paper Title
FACTOR	96.8	97.4	Detecting Deepfakes Without Seeing Any
RealForensics	95.3	97.1	Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detection
AVAD	94.2	94.5	Self-Supervised Video Forensics by Audio-Visual Anomaly Detection
FTCN	92.3	93.1	Exploring Temporal Coherence for More General Video Face Forgery Detection
LipForensics	89.4	91.1	Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detection
AD DFD	88.8	88.1	Joint Audio-Visual Deepfake Detection
Xception	84.8	85.3	FaceForensics++: Learning to Detect Manipulated Facial Images
AVBYOL	73.9	59.2	Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detection
VQGAN	55.0	51.8	Taming Transformers for High-Resolution Image Synthesis
AV-Lip-Sync+	-	-	AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection
Multimodal Ensemble Model	-	-	Lip Sync Matters: A Novel Multimodal Forgery Detector
Avtenet	-	-	AVTENet: Audio-Visual Transformer-based Ensemble Network Exploiting Multiple Experts for Video Deepfake Detection
AV-Lip-Sync Model	-	-	Lip Sync Matters: A Novel Multimodal Forgery Detector

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Deepfake Detection On Fakeavceleb 1 | SOTA | HyperAI