DeepFake Detection

DeepFake Detection is the task of detecting fake videos or images that have been generated using deep learning techniques. Deepfakes are created by using machine learning algorithms to manipulate or replace parts of an original video or image, such as the face of a person. The goal of deepfake detection is to identify such manipulations and distinguish them from real videos or images.

Description source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Image source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 291–300 of 580 papers

Title	Date	Tasks	Status	Hype
GenAI Mirage: The Impostor Bias and the Deepfake Detection Challenge in the Era of Artificial Illusions	Dec 24, 2023	Decision MakingDeepFake Detection	—Unverified	0
Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach	Dec 17, 2023	DeepFake DetectionFace Recognition	CodeCode Available	1
DomainForensics: Exposing Face Forgery across Domains via Bi-directional Adaptation	Dec 17, 2023	DeepFake DetectionDomain Adaptation	—Unverified	0
Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection	Dec 16, 2023	DeepFake DetectionFace Swapping	CodeCode Available	2
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection	Dec 15, 2023	Audio Deepfake DetectionContinual Learning	CodeCode Available	1
AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection	Dec 14, 2023	Adversarial AttackAttribute	CodeCode Available	1
Individualized Deepfake Detection Exploiting Traces Due to Double Neural-Network Operations	Dec 13, 2023	DeepFake DetectionFace Swapping	CodeCode Available	0
Audio Deepfake Detection with Self-Supervised WavLM and Multi-Fusion Attentive Classifier	Dec 13, 2023	Audio Deepfake DetectionDeepFake Detection	—Unverified	0
An adversarial attack approach for eXplainable AI evaluation on deepfake detection models	Dec 8, 2023	Adversarial AttackDeepFake Detection	CodeCode Available	0
DeepFidelity: Perceptual Forgery Fidelity Assessment for Deepfake Detection	Dec 7, 2023	DeepFake DetectionFace Swapping	CodeCode Available	1

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All datasets FakeAVCeleb FaceForensics DFDC 1 CIFAKE: Real and AI-Generated Synthetic Images COCOFake DFFD LAV-DF

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	AV-Lip-Sync+	Accuracy (%)	99.29	—	Unverified
2	Avtenet	Accuracy (%)	98.57	—	Unverified
3	FACTOR	ROC AUC	97.4	—	Unverified
4	RealForensics	ROC AUC	97.1	—	Unverified
5	AVAD	ROC AUC	94.5	—	Unverified
6	AV-Lip-Sync Model	Accuracy (%)	94	—	Unverified
7	FTCN	ROC AUC	93.1	—	Unverified
8	LipForensics	ROC AUC	91.1	—	Unverified
9	Multimodal Ensemble Model	Accuracy (%)	89	—	Unverified
10	AD DFD	ROC AUC	88.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	XceptionNet	DF	96.36	—	Unverified
2	QAD-E	AUC	0.96	—	Unverified
3	EfficientNetB4 + EfficientNetB4ST + B4Att + B4AttST	AUC	0.94	—	Unverified
4	MARLIN (ViT-L)	AUC	0.94	—	Unverified
5	MARLIN (ViT-B)	AUC	0.93	—	Unverified
6	MARLIN (ViT-S)	AUC	0.89	—	Unverified
7	EfficientNetB4 + EfficientNetB4ST + B4AttST	LogLoss	0.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Cross Efficient Vision Transformer	AUC	0.95	—	Unverified
2	Efficient Vision Transformer	AUC	0.92	—	Unverified
3	EfficientNetB4 + EfficientNetB4ST + B4Att	LogLoss	0.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STYLE	0L	99	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FasterThanLies	AUC	99.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FasterThanLies	AUC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FasterThanLies	AUC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BA-TFD	AUC	0.99	—	Unverified