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 526550 of 580 papers

TitleStatusHype
Towards Solving the DeepFake Problem : An Analysis on Improving DeepFake Detection using Dynamic Face AugmentationCode1
Adversarially robust deepfake media detection using fused convolutional neural network predictions0
The Deepfake Detection Dilemma: A Multistakeholder Exploration of Adversarial Dynamics in Synthetic Media0
Fighting deepfakes by detecting GAN DCT anomalies0
Exploring Adversarial Fake Images on Face Manifold0
WildDeepfake: A Challenging Real-World Dataset for Deepfake DetectionCode1
Joint Audio-Visual Deepfake Detection0
Contrastive Self-Supervised Learning of Global-Local Audio-Visual Representations0
Identifying Invariant Texture Violation for Robust Deepfake Detection0
Taming Transformers for High-Resolution Image SynthesisCode1
Learning Self-Consistency for Deepfake DetectionCode1
Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery DetectionCode1
Cost Sensitive Optimization of Deepfake Detector0
Identity-Driven DeepFake Detection0
Adversarial Threats to DeepFake Detection: A Practical Perspective0
Spatio-temporal Features for Generalized Detection of Deepfake Videos0
Neural Deepfake Detection with Factual Structure of TextCode1
DeepFakesON-Phys: DeepFakes Detection based on Heart Rate EstimationCode1
Dodging DeepFake Detection via Implicit Spatial-Domain Notch Filtering0
A Convolutional LSTM based Residual Network for Deepfake Video DetectionCode1
Deepfake detection: humans vs. machines0
DeepFake Detection Based on the Discrepancy Between the Face and its Context0
On Attribution of Deepfakes0
Two-branch Recurrent Network for Isolating Deepfakes in Videos0
Fighting Deepfake by Exposing the Convolutional Traces on Images0
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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