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 351–400 of 580 papers

TitleStatusHype
DeepfakeBench: A Comprehensive Benchmark of Deepfake DetectionCode3
Improving Fairness in Deepfake DetectionCode1
Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and LocalizationCode1
TranssionADD: A multi-frame reinforcement based sequence tagging model for audio deepfake detection—0
Searching for the Fakes: Efficient Neural Architecture Search for General Face Forgery Detection—0
NPVForensics: Jointing Non-critical Phonemes and Visemes for Deepfake Detection—0
UNTAG: LEARNING GENERIC FEATURES FOR UNSUPERVISED TYPE-AGNOSTIC DEEPFAKE DETECTIONCode0
Improved DeepFake Detection Using Whisper FeaturesCode1
DeepFake-Adapter: Dual-Level Adapter for DeepFake DetectionCode1
Betray Oneself: A Novel Audio DeepFake Detection Model via Mono-to-Stereo ConversionCode0
Introducing Explicit Gaze Constraints to Face Swapping—0
Undercover Deepfakes: Detecting Fake Segments in VideosCode1
SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake DetectionCode1
Fooling State-of-the-Art Deepfake Detection with High-Quality Deepfakes—0
Bts-e: Audio deepfake detection using breathing-talking-silence encoderCode1
Glitch in the Matrix: A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and LocalizationCode1
Can deepfakes be created by novice users?—0
UCF: Uncovering Common Features for Generalizable Deepfake DetectionCode3
Evading DeepFake Detectors via Adversarial Statistical Consistency—0
PTW: Pivotal Tuning Watermarking for Pre-Trained Image GeneratorsCode1
Investigation of ensemble methods for the detection of deepfake face manipulations—0
Assessment Framework for Deepfake Detection in Real-world Situations—0
Deepfake Detection of Occluded Images Using a Patch-based Approach—0
Deepfake Detection with Deep Learning: Convolutional Neural Networks versus Transformers—0
Detecting and Grounding Multi-Modal Media ManipulationCode2
Leveraging Deep Learning Approaches for Deepfake Detection: A Review—0
Parents and Children: Distinguishing Multimodal DeepFakes from Natural ImagesCode1
Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection—0
LatentForensics: Towards frugal deepfake detection in the StyleGAN latent space—0
Impact of Video Processing Operations in Deepfake Detection—0
Real Face Foundation Representation Learning for Generalized Deepfake Detection—0
Mover: Mask and Recovery based Facial Part Consistency Aware Method for Deepfake Video Detection—0
Level Up the Deepfake Detection: a Method to Effectively Discriminate Images Generated by GAN Architectures and Diffusion Models—0
Benchmarking Deepart Detection—0
Masked Relation Learning for DeepFake DetectionCode1
Learning Pairwise Interaction for Generalizable DeepFake DetectionCode0
Why Do Facial Deepfake Detectors Fail?—0
Mitigating Adversarial Attacks in Deepfake Detection: An Exploration of Perturbation and AI Techniques—0
Visual Realism Assessment for Face-swap VideosCode0
Deepfake Detection Analyzing Hybrid Dataset Utilizing CNN and SVM—0
ISTVT: Interpretable Spatial-Temporal Video Transformer for Deepfake DetectionCode1
Deepfake Detection using Biological Features: A Survey—0
Self-Supervised Video Forensics by Audio-Visual Anomaly DetectionCode1
Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View—0
AUNet: Learning Relations Between Action Units for Face Forgery Detection—0
DF-Platter: Multi-Face Heterogeneous Deepfake Dataset—0
Dynamic Graph Learning With Content-Guided Spatial-Frequency Relation Reasoning for Deepfake Detection—0
Defense Against Adversarial Attacks on Audio DeepFake DetectionCode1
Fighting Malicious Media Data: A Survey on Tampering Detection and Deepfake Detection—0
Testing Human Ability To Detect Deepfake Images of Human FacesCode0
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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