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 176200 of 580 papers

TitleStatusHype
Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding ApproachCode0
Robust AI-Generated Face Detection with Imbalanced DataCode0
Rehearsal with Auxiliary-Informed Sampling for Audio Deepfake DetectionCode0
WWW: Where, Which and Whatever Enhancing Interpretability in Multimodal Deepfake DetectionCode0
Penny-Wise and Pound-Foolish in Deepfake DetectionCode0
Deepfake Detection by Human Crowds, Machines, and Machine-informed CrowdsCode0
PolyGlotFake: A Novel Multilingual and Multimodal DeepFake DatasetCode0
Are Watermarks Bugs for Deepfake Detectors? Rethinking Proactive ForensicsCode0
Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social NetworksCode0
Practical Manipulation Model for Robust Deepfake DetectionCode0
Open-Set Deepfake Detection: A Parameter-Efficient Adaptation Method with Forgery Style MixtureCode0
One-Class Learning with Adaptive Centroid Shift for Audio Deepfake DetectionCode0
Preserving AUC Fairness in Learning with Noisy Protected GroupsCode0
CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake DetectionCode0
Neural Codec Source Tracing: Toward Comprehensive Attribution in Open-Set ConditionCode0
Multiverse Through Deepfakes: The MultiFakeVerse Dataset of Person-Centric Visual and Conceptual ManipulationsCode0
Characterizing the temporal dynamics of universal speech representations for generalizable deepfake detectionCode0
LoRAX: LoRA eXpandable Networks for Continual Synthetic Image AttributionCode0
Measuring the Robustness of Audio Deepfake DetectorsCode0
Learning Pairwise Interaction for Generalizable DeepFake DetectionCode0
CAMME: Adaptive Deepfake Image Detection with Multi-Modal Cross-AttentionCode0
2D-Malafide: Adversarial Attacks Against Face Deepfake Detection SystemsCode0
Individualized Deepfake Detection Exploiting Traces Due to Double Neural-Network OperationsCode0
Improving the Perturbation-Based Explanation of Deepfake Detectors Through the Use of Adversarially-Generated SamplesCode0
Block shuffling learning for Deepfake DetectionCode0
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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