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 201–250 of 580 papers

TitleStatusHype
0/1 Deep Neural Networks via Block Coordinate Descent—0
Fake It till You Make It: Curricular Dynamic Forgery Augmentations towards General Deepfake Detection—0
Multiple Contexts and Frequencies Aggregation Network forDeepfake Detection—0
AASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge—0
Facial Forgery-based Deepfake Detection using Fine-Grained Features—0
Comparative Analysis of Deepfake Detection Models: New Approaches and Perspectives—0
Comparative Analysis of Deep-Fake Algorithms—0
Adversarially robust deepfake media detection using fused convolutional neural network predictions—0
Fairness Evaluation in Deepfake Detection Models using Metamorphic Testing—0
DFCon: Attention-Driven Supervised Contrastive Learning for Robust Deepfake Detection—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 Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality—0
Detecting Deepfake Videos: An Analysis of Three Techniques—0
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio—0
DF-Platter: Multi-Face Heterogeneous Deepfake Dataset—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
Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Models—0
Complex-valued neural networks for voice anti-spoofing—0
Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning—0
OGAN: Disrupting Deepfakes with an Adversarial Attack that Survives Training—0
Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities—0
Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption—0
Does Audio Deepfake Detection Generalize?—0
Continuous fake media detection: adapting deepfake detectors to new generative techniques—0
Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies—0
A Quality-Centric Framework for Generic Deepfake Detection—0
Classifying Deepfakes Using Swin Transformers—0
Dynamic Graph Learning With Content-Guided Spatial-Frequency Relation Reasoning for Deepfake Detection—0
A Preliminary Exploration with GPT-4o Voice Mode—0
ED^4: Explicit Data-level Debiasing for Deepfake Detection—0
DepthFake: a depth-based strategy for detecting Deepfake videos—0
Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors—0
FaceShield: Defending Facial Image against Deepfake Threats—0
Delving into the Frequency: Temporally Consistent Human Motion Transfer in the Fourier Space—0
Delving into Sequential Patches for Deepfake Detection—0
Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces—0
EnvSDD: Benchmarking Environmental Sound Deepfake Detection—0
Evading DeepFake Detectors via Adversarial Statistical Consistency—0
Advancing High Fidelity Identity Swapping for Forgery Detection—0
DeFakePro: Decentralized DeepFake Attacks Detection using ENF Authentication—0
Capture Artifacts via Progressive Disentangling and Purifying Blended Identities for Deepfake Detection—0
DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms—0
Can Multi-modal (reasoning) LLMs work as deepfake detectors?—0
A Novel Framework for Assessment of Learning-based Detectors in Realistic Conditions with Application to Deepfake Detection—0
Exploiting Style Latent Flows for Generalizing Deepfake Video Detection—0
A3:Ambiguous Aberrations Captured via Astray-Learning for Facial Forgery Semantic Sublimation—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