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

Showing 251275 of 580 papers

TitleStatusHype
REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations0
Deepfake Detection of Singing Voices With Whisper Encodings0
DFCon: Attention-Driven Supervised Contrastive Learning for Robust Deepfake Detection0
Extending Information Bottleneck Attribution to Video SequencesCode0
Classifying Deepfakes Using Swin Transformers0
Generalizable Audio Deepfake Detection via Latent Space Refinement and Augmentation0
What Does an Audio Deepfake Detector Focus on? A Study in the Time Domain0
GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection0
Audio-Visual Deepfake Detection With Local Temporal Inconsistencies0
Neural Codec Source Tracing: Toward Comprehensive Attribution in Open-Set ConditionCode0
Exploring Unbiased Deepfake Detection via Token-Level Shuffling and Mixing0
Towards Interactive Deepfake AnalysisCode0
FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing0
Inclusion 2024 Global Multimedia Deepfake Detection Challenge: Towards Multi-dimensional Face Forgery Detection0
Investigating Prosodic Signatures via Speech Pre-Trained Models for Audio Deepfake Source Attribution0
Data-Driven Fairness Generalization for Deepfake Detection0
FRIDAY: Mitigating Unintentional Facial Identity in Deepfake Detectors Guided by Facial Recognizers0
GLCF: A Global-Local Multimodal Coherence Analysis Framework for Talking Face Generation Detection0
Phoneme-Level Feature Discrepancies: A Key to Detecting Sophisticated Speech Deepfakes0
Towards a Universal Synthetic Video Detector: From Face or Background Manipulations to Fully AI-Generated Content0
Is it the model or the metric -- On robustness measures of deeplearning models0
FaceShield: Defending Facial Image against Deepfake Threats0
Spoofing-Robust Speaker Verification Based on Time-Domain Embedding0
Audios Don't Lie: Multi-Frequency Channel Attention Mechanism for Audio Deepfake Detection0
Nearly Solved? Robust Deepfake Detection Requires More than Visual Forensics0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AV-Lip-Sync+Accuracy (%)99.29Unverified
2AvtenetAccuracy (%)98.57Unverified
3FACTORROC AUC97.4Unverified
4RealForensicsROC AUC97.1Unverified
5AVADROC AUC94.5Unverified
6AV-Lip-Sync ModelAccuracy (%)94Unverified
7FTCNROC AUC93.1Unverified
8LipForensicsROC AUC91.1Unverified
9Multimodal Ensemble ModelAccuracy (%)89Unverified
10AD DFDROC AUC88.1Unverified
#ModelMetricClaimedVerifiedStatus
1XceptionNetDF96.36Unverified
2QAD-EAUC0.96Unverified
3EfficientNetB4 + EfficientNetB4ST + B4Att + B4AttSTAUC0.94Unverified
4MARLIN (ViT-L)AUC0.94Unverified
5MARLIN (ViT-B)AUC0.93Unverified
6MARLIN (ViT-S)AUC0.89Unverified
7EfficientNetB4 + EfficientNetB4ST + B4AttSTLogLoss0.33Unverified
#ModelMetricClaimedVerifiedStatus
1Cross Efficient Vision TransformerAUC0.95Unverified
2Efficient Vision TransformerAUC0.92Unverified
3EfficientNetB4 + EfficientNetB4ST + B4AttLogLoss0.46Unverified
#ModelMetricClaimedVerifiedStatus
1STYLE0L99Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC99.65Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1Unverified
#ModelMetricClaimedVerifiedStatus
1BA-TFDAUC0.99Unverified