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

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Showing 201–225 of 580 papers

TitleStatusHype
Adversarially robust deepfake media detection using fused convolutional neural network predictions—0
Comparative Analysis of Deep Convolutional Neural Networks for Detecting Medical Image Deepfakes—0
A Review of Deep Learning-based Approaches for Deepfake Content Detection—0
Detecting Deepfake Videos: An Analysis of Three Techniques—0
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio—0
Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Models—0
Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning—0
Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption—0
Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies—0
Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality—0
A Quality-Centric Framework for Generic Deepfake Detection—0
Classifying Deepfakes Using Swin Transformers—0
DFCon: Attention-Driven Supervised Contrastive Learning for Robust Deepfake Detection—0
A Preliminary Exploration with GPT-4o Voice Mode—0
DepthFake: a depth-based strategy for detecting Deepfake videos—0
EnvSDD: Benchmarking Environmental Sound Deepfake Detection—0
DF-TransFusion: Multimodal Deepfake Detection via Lip-Audio Cross-Attention and Facial Self-Attention—0
Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection—0
ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis—0
Diffusion Deepfake—0
Delving into the Frequency: Temporally Consistent Human Motion Transfer in the Fourier Space—0
Complex-valued neural networks for voice anti-spoofing—0
Delving into Sequential Patches for Deepfake Detection—0
OGAN: Disrupting Deepfakes with an Adversarial Attack that Survives Training—0
Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces—0
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All datasetsFakeAVCelebFaceForensicsDFDC1CIFAKE: Real and AI-Generated Synthetic ImagesCOCOFakeDFFDLAV-DF

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AV-Lip-Sync+Accuracy (%)99.29—Unverified
2AvtenetAccuracy (%)98.57—Unverified
3FACTORROC AUC97.4—Unverified
4RealForensicsROC AUC97.1—Unverified
5AVADROC AUC94.5—Unverified
6AV-Lip-Sync ModelAccuracy (%)94—Unverified
7FTCNROC AUC93.1—Unverified
8LipForensicsROC AUC91.1—Unverified
9Multimodal Ensemble ModelAccuracy (%)89—Unverified
10AD DFDROC AUC88.1—Unverified
#ModelMetricClaimedVerifiedStatus
1XceptionNetDF96.36—Unverified
2QAD-EAUC0.96—Unverified
3EfficientNetB4 + EfficientNetB4ST + B4Att + B4AttSTAUC0.94—Unverified
4MARLIN (ViT-L)AUC0.94—Unverified
5MARLIN (ViT-B)AUC0.93—Unverified
6MARLIN (ViT-S)AUC0.89—Unverified
7EfficientNetB4 + EfficientNetB4ST + B4AttSTLogLoss0.33—Unverified
#ModelMetricClaimedVerifiedStatus
1Cross Efficient Vision TransformerAUC0.95—Unverified
2Efficient Vision TransformerAUC0.92—Unverified
3EfficientNetB4 + EfficientNetB4ST + B4AttLogLoss0.46—Unverified
#ModelMetricClaimedVerifiedStatus
1STYLE0L99—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC99.65—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1—Unverified
#ModelMetricClaimedVerifiedStatus
1BA-TFDAUC0.99—Unverified