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 251–300 of 580 papers

TitleStatusHype
MAVOS-DD: Multilingual Audio-Video Open-Set Deepfake Detection Benchmark—0
A3:Ambiguous Aberrations Captured via Astray-Learning for Facial Forgery Semantic Sublimation—0
AASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge—0
A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations—0
ADD 2022: the First Audio Deep Synthesis Detection Challenge—0
ADD 2023: Towards Audio Deepfake Detection and Analysis in the Wild—0
A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures—0
Advancing High Fidelity Identity Swapping for Forgery Detection—0
Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning—0
Adversarially robust deepfake media detection using fused convolutional neural network predictions—0
Adversarial Threats to DeepFake Detection: A Practical Perspective—0
Investigating the Impact of Pre-processing and Prediction Aggregation on the DeepFake Detection Task—0
A Hybrid CNN-LSTM model for Video Deepfake Detection by Leveraging Optical Flow Features—0
A Hybrid Quantum-Classical AI-Based Detection Strategy for Generative Adversarial Network-Based Deepfake Attacks on an Autonomous Vehicle Traffic Sign Classification System—0
GenAI Mirage: The Impostor Bias and the Deepfake Detection Challenge in the Era of Artificial Illusions—0
A Machine Learning Approach for DeepFake Detection—0
A Multimodal Framework for Deepfake Detection—0
Analyzing the Impact of Splicing Artifacts in Partially Fake Speech Signals—0
A New Approach to Improve Learning-based Deepfake Detection in Realistic Conditions—0
An Examination of Fairness of AI Models for Deepfake Detection—0
An Experimental Evaluation on Deepfake Detection using Deep Face Recognition—0
Anisotropic multiresolution analyses for deepfake detection—0
Anomaly Detection and Localization for Speech Deepfakes via Feature Pyramid Matching—0
A Note on Deepfake Detection with Low-Resources—0
A novel approach for detecting deep fake videos using graph neural network—0
A Novel Framework for Assessment of Learning-based Detectors in Realistic Conditions with Application to Deepfake Detection—0
A Preliminary Exploration with GPT-4o Voice Mode—0
A Quality-Centric Framework for Generic Deepfake Detection—0
Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Models—0
A Review of Deep Learning-based Approaches for Deepfake Content Detection—0
ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis—0
ASASVIcomtech: The Vicomtech-UGR Speech Deepfake Detection and SASV Systems for the ASVspoof5 Challenge—0
Assessment Framework for Deepfake Detection in Real-world Situations—0
A Timely Survey on Vision Transformer for Deepfake Detection—0
Attacker Attribution of Audio Deepfakes—0
Audio Deepfake Detection Based on a Combination of F0 Information and Real Plus Imaginary Spectrogram Features—0
Audio Deepfake Detection with Self-Supervised WavLM and Multi-Fusion Attentive Classifier—0
Audios Don't Lie: Multi-Frequency Channel Attention Mechanism for Audio Deepfake Detection—0
Audio-Visual Deepfake Detection With Local Temporal Inconsistencies—0
AUNet: Learning Relations Between Action Units for Face Forgery Detection—0
AuthGuard: Generalizable Deepfake Detection via Language Guidance—0
Automated Deepfake Detection—0
AVFF: Audio-Visual Feature Fusion for Video Deepfake Detection—0
AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection—0
AVTENet: Audio-Visual Transformer-based Ensemble Network Exploiting Multiple Experts for Video Deepfake Detection—0
Benchmarking Audio Deepfake Detection Robustness in Real-world Communication Scenarios—0
Benchmarking Deepart Detection—0
Benchmarking Foundation Models for Zero-Shot Biometric Tasks—0
Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cues—0
Beyond Face Swapping: A Diffusion-Based Digital Human Benchmark for Multimodal 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