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 476500 of 580 papers

TitleStatusHype
Leveraging Real Talking Faces via Self-Supervision for Robust Forgery DetectionCode1
TAFIM: Targeted Adversarial Attacks against Facial Image ManipulationsCode1
ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake ImagesCode0
Contrastive Learning of Global and Local Video Representations0
A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures0
FakeTransformer: Exposing Face Forgery From Spatial-Temporal Representation Modeled By Facial Pixel Variations0
Impact of Benign Modifications on Discriminative Performance of Deepfake Detectors0
WaveFake: A Data Set to Facilitate Audio Deepfake DetectionCode1
Explaining deep learning models for spoofing and deepfake detection with SHapley Additive exPlanationsCode1
MC-LCR: Multi-modal contrastive classification by locally correlated representations for effective face forgery detection0
An Experimental Evaluation on Deepfake Detection using Deep Face Recognition0
Machine Learning based Medical Image Deepfake Detection: A Comparative Study0
Finding Facial Forgery Artifacts with Parts-Based Detectors0
MD-CSDNetwork: Multi-Domain Cross Stitched Network for Deepfake Detection0
FaceGuard: Proactive Deepfake Detection0
Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors0
DeepFake Detection with Inconsistent Head Poses: Reproducibility and Analysis0
DeepFake MNIST+: A DeepFake Facial Animation DatasetCode1
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection0
Exploring Temporal Coherence for More General Video Face Forgery DetectionCode1
Video Transformer for Deepfake Detection with Incremental Learning0
FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake DatasetCode1
End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake DetectionCode1
Human Perception of Audio Deepfakes0
Combining EfficientNet and Vision Transformers for Video Deepfake DetectionCode1
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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