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
A3:Ambiguous Aberrations Captured via Astray-Learning for Facial Forgery Semantic Sublimation0
GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection0
Deep Learning Technology for Face Forgery Detection: A Survey0
Deep Learning for Deepfakes Creation and Detection: A Survey0
Can deepfakes be created by novice users?0
DeePhy: On Deepfake Phylogeny0
A novel approach for detecting deep fake videos using graph neural network0
Deepfake Video Forensics based on Transfer Learning0
A Note on Deepfake Detection with Low-Resources0
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation0
A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures0
FractalForensics: Proactive Deepfake Detection and Localization via Fractal Watermarks0
DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning0
Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forward0
Deepfakes Detection with Automatic Face Weighting0
Anomaly Detection and Localization for Speech Deepfakes via Feature Pyramid Matching0
DeepFake-o-meter: An Open Platform for DeepFake Detection0
Anisotropic multiresolution analyses for deepfake detection0
MAVOS-DD: Multilingual Audio-Video Open-Set Deepfake Detection Benchmark0
0-1 laws for pattern occurrences in phylogenetic trees and networks0
FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbations0
Deepfake Media Forensics: State of the Art and Challenges Ahead0
Mover: Mask and Recovery based Facial Part Consistency Aware Method for Deepfake Video Detection0
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection0
An Experimental Evaluation on Deepfake Detection using Deep Face Recognition0
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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