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 401425 of 580 papers

TitleStatusHype
A Dataless FaceSwap Detection Approach Using Synthetic ImagesCode0
FakeOut: Leveraging Out-of-domain Self-supervision for Multi-modal Video Deepfake DetectionCode1
Deepfake Detection via Joint Unsupervised Reconstruction and Supervised Classification0
Deepfake Detection: A Comprehensive Survey from the Reliability Perspective0
MINTIME: Multi-Identity Size-Invariant Video Deepfake DetectionCode1
Generalizable Deepfake Detection with Phase-Based Motion Analysis0
MARLIN: Masked Autoencoder for facial video Representation LearnINgCode2
Lip Sync Matters: A Novel Multimodal Forgery DetectorCode0
Cross-Domain Local Characteristic Enhanced Deepfake Video Detection0
Exploring Spatial-Temporal Features for Deepfake Detection and LocalizationCode1
Anisotropic multiresolution analyses for deepfake detection0
Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection GeneralizationCode1
Deepfake Detection System for the ADD Challenge Track 3.2 Based on Score Fusion0
GOTCHA: Real-Time Video Deepfake Detection via Challenge-ResponseCode1
SpecRNet: Towards Faster and More Accessible Audio DeepFake DetectionCode1
Aggregating Layers for Deepfake DetectionCode0
A Machine Learning Approach for DeepFake Detection0
When Handcrafted Features and Deep Features Meet Mismatched Training and Test Sets for Deepfake Detection0
DeePhy: On Deepfake Phylogeny0
Multimodal Graph Learning for Deepfake Detection0
Deep Convolutional Pooling Transformer for Deepfake DetectionCode0
Protecting World Leader Using Facial Speaking Pattern Against Deepfakes0
Delving into the Frequency: Temporally Consistent Human Motion Transfer in the Fourier Space0
DepthFake: a depth-based strategy for detecting Deepfake videos0
Deepfake Detection using ImageNet models and Temporal Images of 468 Facial Landmarks0
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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