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 501525 of 580 papers

TitleStatusHype
Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities0
Fake It till You Make It: Curricular Dynamic Forgery Augmentations towards General Deepfake Detection0
Dodging DeepFake Detection via Implicit Spatial-Domain Notch Filtering0
FakeTransformer: Exposing Face Forgery From Spatial-Temporal Representation Modeled By Facial Pixel Variations0
FauForensics: Boosting Audio-Visual Deepfake Detection with Facial Action Units0
Fighting Deepfake by Exposing the Convolutional Traces on Images0
Fighting deepfakes by detecting GAN DCT anomalies0
Fighting Malicious Media Data: A Survey on Tampering Detection and Deepfake Detection0
Finding Facial Forgery Artifacts with Parts-Based Detectors0
Fooling State-of-the-Art Deepfake Detection with High-Quality Deepfakes0
Forensic deepfake audio detection using segmental speech features0
FractalForensics: Proactive Deepfake Detection and Localization via Fractal Watermarks0
FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbations0
FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge0
FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing0
FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning0
FRIDAY: Mitigating Unintentional Facial Identity in Deepfake Detectors Guided by Facial Recognizers0
From Sharpness to Better Generalization for Speech Deepfake Detection0
GazeForensics: DeepFake Detection via Gaze-guided Spatial Inconsistency Learning0
GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection0
Generalizable Audio Deepfake Detection via Latent Space Refinement and Augmentation0
Generalizable Deepfake Detection with Phase-Based Motion Analysis0
Generalizable speech deepfake detection via meta-learned LoRA0
GLCF: A Global-Local Multimodal Coherence Analysis Framework for Talking Face Generation Detection0
GROOT: Generating Robust Watermark for Diffusion-Model-Based Audio Synthesis0
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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