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 301325 of 580 papers

TitleStatusHype
Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap0
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles0
Towards a Universal Synthetic Video Detector: From Face or Background Manipulations to Fully AI-Generated Content0
Towards Benchmarking and Evaluating Deepfake Detection0
Towards General Deepfake Detection with Dynamic Curriculum0
Towards generalisable and calibrated synthetic speech detection with self-supervised representations0
Towards Generalizable Deepfake Detection by Primary Region Regularization0
Towards Generalizable Deepfake Detection with Spatial-Frequency Collaborative Learning and Hierarchical Cross-Modal Fusion0
Towards Generalizable Deepfake Detection with Locality-aware AutoEncoder0
Towards General Visual-Linguistic Face Forgery Detection0
Towards Measuring Fairness in AI: the Casual Conversations Dataset0
Towards mitigating uncann(eye)ness in face swaps via gaze-centric loss terms0
Towards Open-world Generalized Deepfake Detection: General Feature Extraction via Unsupervised Domain Adaptation0
Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View0
Toward Transdisciplinary Approaches to Audio Deepfake Discernment0
Training-Free Deepfake Voice Recognition by Leveraging Large-Scale Pre-Trained Models0
TranssionADD: A multi-frame reinforcement based sequence tagging model for audio deepfake detection0
TruthLens:A Training-Free Paradigm for DeepFake Detection0
TruthLens: Explainable DeepFake Detection for Face Manipulated and Fully Synthetic Data0
Two-branch Recurrent Network for Isolating Deepfakes in Videos0
Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models0
Understanding Audiovisual Deepfake Detection: Techniques, Challenges, Human Factors and Perceptual Insights0
Understanding the Security of Deepfake Detection0
Unearthing Common Inconsistency for Generalisable Deepfake Detection0
Unexploited Information Value in Human-AI Collaboration0
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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