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 251275 of 580 papers

TitleStatusHype
Texture, Shape and Order Matter: A New Transformer Design for Sequential DeepFake Detection0
FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge0
DeepFake-O-Meter v2.0: An Open Platform for DeepFake DetectionCode3
Towards More General Video-based Deepfake Detection through Facial Feature Guided Adaptation for Foundation ModelCode1
Cross-Domain Audio Deepfake Detection: Dataset and Analysis0
D^3: Scaling Up Deepfake Detection by Learning from DiscrepancyCode1
Diffusion Deepfake0
Heterogeneity over Homogeneity: Investigating Multilingual Speech Pre-Trained Models for Detecting Audio DeepfakeCode0
AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting StrategiesCode1
Exploring Green AI for Audio Deepfake DetectionCode0
Can ChatGPT Detect DeepFakes? A Study of Using Multimodal Large Language Models for Media ForensicsCode1
Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns InjectionCode0
Selective Domain-Invariant Feature for Generalizable Deepfake Detection0
Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake DetectionCode2
Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space LearningCode2
Exploiting Style Latent Flows for Generalizing Deepfake Video Detection0
Data-Independent Operator: A Training-Free Artifact Representation Extractor for Generalizable Deepfake DetectionCode1
XAI-Based Detection of Adversarial Attacks on Deepfake DetectorsCode0
Exposing the Deception: Uncovering More Forgery Clues for Deepfake DetectionCode2
Preserving Fairness Generalization in Deepfake DetectionCode2
CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake DetectionCode0
Deepfake Detection and the Impact of Limited Computing CapabilitiesCode0
0-1 laws for pattern occurrences in phylogenetic trees and networks0
Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning0
Towards mitigating uncann(eye)ness in face swaps via gaze-centric loss terms0
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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