SOTAVerified

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

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Showing 201–250 of 580 papers

TitleStatusHype
Deepfake Media Forensics: State of the Art and Challenges Ahead—0
Contrasting Deepfakes Diffusion via Contrastive Learning and Global-Local SimilaritiesCode2
LookupForensics: A Large-Scale Multi-Task Dataset for Multi-Phase Image-Based Fact Verification—0
UniForensics: Face Forgery Detection via General Facial Representation—0
SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection—0
Statistics-aware Audio-visual Deepfake Detector—0
GROOT: Generating Robust Watermark for Diffusion-Model-Based Audio Synthesis—0
Exploring the Impact of Moire Pattern on Deepfake Detectors—0
Targeted Augmented Data for Audio Deepfake Detection—0
Adversarial Magnification to Deceive Deepfake Detection through Super ResolutionCode1
Deepfake Audio Detection Using Spectrogram-based Feature and Ensemble of Deep Learning Models—0
GM-DF: Generalized Multi-Scenario Deepfake DetectionCode0
One-Class Learning with Adaptive Centroid Shift for Audio Deepfake DetectionCode0
PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection—0
A Multi-Stream Fusion Approach with One-Class Learning for Audio-Visual Deepfake DetectionCode0
DF40: Toward Next-Generation Deepfake DetectionCode3
Media Forensics and Deepfake Systematic Survey—0
Straight Through Gumbel Softmax Estimator based Bimodal Neural Architecture Search for Audio-Visual Deepfake Detection—0
Decoupling Forgery Semantics for Generalizable Deepfake DetectionCode0
Real-Time Deepfake Detection in the Real-World—0
Continuous fake media detection: adapting deepfake detectors to new generative techniques—0
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio—0
Evolving from Single-modal to Multi-modal Facial Deepfake Detection: A SurveyCode3
Faster Than Lies: Real-time Deepfake Detection using Binary Neural NetworksCode2
Harder or Different? Understanding Generalization of Audio Deepfake Detection—0
Singing Voice Graph Modeling for SingFake DetectionCode1
Generalized Source Tracing: Detecting Novel Audio Deepfake Algorithm with Real Emphasis and Fake Dispersion StrategyCode1
AVFF: Audio-Visual Feature Fusion for Video Deepfake Detection—0
CtrSVDD: A Benchmark Dataset and Baseline Analysis for Controlled Singing Voice Deepfake DetectionCode1
DistilDIRE: A Small, Fast, Cheap and Lightweight Diffusion Synthesized Deepfake DetectionCode1
DeMamba: AI-Generated Video Detection on Million-Scale GenVideo BenchmarkCode2
Text Modality Oriented Image Feature Extraction for Detecting Diffusion-based DeepFake—0
A3:Ambiguous Aberrations Captured via Astray-Learning for Facial Forgery Semantic Sublimation—0
A Timely Survey on Vision Transformer for Deepfake Detection—0
EEG-Features for Generalized Deepfake Detection—0
PolyGlotFake: A Novel Multilingual and Multimodal DeepFake DatasetCode0
UnMarker: A Universal Attack on Defensive Image WatermarkingCode3
SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge Evaluation PlanCode1
The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake AudioCode2
Detecting music deepfakes is easy but actually hardCode2
Unmasking Illusions: Understanding Human Perception of Audiovisual Deepfakes—0
Training-Free Deepfake Voice Recognition by Leveraging Large-Scale Pre-Trained Models—0
Exploring Self-Supervised Vision Transformers for Deepfake Detection: A Comparative AnalysisCode0
In Anticipation of Perfect Deepfake: Identity-anchored Artifact-agnostic Detection under Rebalanced Deepfake Detection Protocol—0
Explicit Correlation Learning for Generalizable Cross-Modal Deepfake DetectionCode1
Towards Quantitative Evaluation of Explainable AI Methods for Deepfake DetectionCode0
Are Watermarks Bugs for Deepfake Detectors? Rethinking Proactive ForensicsCode0
Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities—0
CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive LearningCode1
Retrieval-Augmented Audio Deepfake Detection—0
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All datasetsFakeAVCelebFaceForensicsDFDC1CIFAKE: Real and AI-Generated Synthetic ImagesCOCOFakeDFFDLAV-DF

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AV-Lip-Sync+Accuracy (%)99.29—Unverified
2AvtenetAccuracy (%)98.57—Unverified
3FACTORROC AUC97.4—Unverified
4RealForensicsROC AUC97.1—Unverified
5AVADROC AUC94.5—Unverified
6AV-Lip-Sync ModelAccuracy (%)94—Unverified
7FTCNROC AUC93.1—Unverified
8LipForensicsROC AUC91.1—Unverified
9Multimodal Ensemble ModelAccuracy (%)89—Unverified
10AD DFDROC AUC88.1—Unverified
#ModelMetricClaimedVerifiedStatus
1XceptionNetDF96.36—Unverified
2QAD-EAUC0.96—Unverified
3EfficientNetB4 + EfficientNetB4ST + B4Att + B4AttSTAUC0.94—Unverified
4MARLIN (ViT-L)AUC0.94—Unverified
5MARLIN (ViT-B)AUC0.93—Unverified
6MARLIN (ViT-S)AUC0.89—Unverified
7EfficientNetB4 + EfficientNetB4ST + B4AttSTLogLoss0.33—Unverified
#ModelMetricClaimedVerifiedStatus
1Cross Efficient Vision TransformerAUC0.95—Unverified
2Efficient Vision TransformerAUC0.92—Unverified
3EfficientNetB4 + EfficientNetB4ST + B4AttLogLoss0.46—Unverified
#ModelMetricClaimedVerifiedStatus
1STYLE0L99—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC99.65—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1—Unverified
#ModelMetricClaimedVerifiedStatus
1BA-TFDAUC0.99—Unverified