Deepfake Detection on DFDC
100AUCFACTOR
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| FACTORScenario=In-Method, Train/Test=B/B2023.11 | 100 | — | — | |
| FACTORScenario=Zero-Day, Train/Test=A/B2023.11 | 100 | — | — | |
| FACTORScenario=In-Method, Train/Test=A/A2023.11 | 99.9 | — | — | |
| FACTORScenario=Zero-Day, Train/Test=B/A2023.11 | 99.9 | — | — | |
| FACTOREvaluation Protocol=Ref. Set, Reference Set Source=50% subset of training videos2023.11 | 99.7 | — | — | |
| F3NETScenario=In-Method, Train/Test=A/A2023.11 | 97.4 | — | — | |
| UCFScenario=In-Method, Train/Test=A/A2023.11 | 97 | — | — | |
| Aletheia2026.04 | 96.6 | — | — | |
| SPSLScenario=In-Method, Train/Test=A/A2023.11 | 96.4 | — | — | |
| FFDScenario=In-Method, Train/Test=A/A2023.11 | 96 | — | — | |
| DF40 baseline2026.04 | 96 | — | — | |
| XceptionScenario=In-Method, Train/Test=A/A2023.11 | 95.7 | — | — | |
| LAA-Net2026.04 | 95.5 | — | — | |
| RECCEScenario=In-Method, Train/Test=A/A2023.11 | 95 | — | — | |
| UCFScenario=In-Method, Train/Test=B/B2023.11 | 94.9 | — | — | |
| Xception baseline2026.04 | 94.1 | — | — | |
| XceptionScenario=In-Method, Train/Test=B/B2023.11 | 93.2 | — | — | |
| F3NETScenario=In-Method, Train/Test=B/B2023.11 | 89.4 | — | — | |
| RECCEScenario=In-Method, Train/Test=B/B2023.11 | 88.6 | — | — | |
| F3NETScenario=Zero-Day, Train/Test=B/A2023.11 | 87.9 | — | — | |
| M2F2-Det (w/ SBI)Training set (Real)=true, Training set (Fake)=false2025.03 | 87.8 | — | — | |
| FreqBlenderVenue=NeurIPS24, Training set (Real)=true, Training set (Fake)=false2025.03 | 87.56 | — | — | |
| ForAdaTraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 87.2 | — | — | |
| ForAdaInput=Frame, Backbone=CLIP ViT-L/14, Training Dataset=FF++2025.08 | 87.2 | — | — | |
| GenD (CLIP)Input=Frame, Backbone=CLIP ViT-L/14, Training Dataset=FF++2025.08 | 87.1 | — | — | |
| LAA-Net (w/ SBI)Venue=CVPR24, Training set (Real)=true, Training set (Fake)=false2025.03 | 86.94 | — | — | |
| LAA-NetInput=Frame, Backbone=EFNB4, Training Dataset=FF++2025.08 | 86.9 | — | — | |
| HAADTraining Dataset=FF++, Evaluation Protocol=Cross-dataset Evaluation2026.05 | 86.8 | — | — | |
| SePLTraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 86.6 | — | — | |
| SeeableVenue=ICCV23, Training set (Real)=true, Training set (Fake)=false2025.03 | 86.3 | — | — | |
| ViT-Forensics2025.11 | 86.2 | — | — | |
| AUNetVenue=CVPR23, Training set (Real)=true, Training set (Fake)=false2025.03 | 86.16 | — | — | |
| SBIVenue=CVPR22, Training set (Real)=true, Training set (Fake)=false2025.03 | 86.15 | — | — | |
| FFDScenario=In-Method, Train/Test=B/B2023.11 | 85.7 | — | — | |
| INSIGHT2025.11 | 85.7 | — | — | |
| ForAdaTraining Data=FF++, Evaluation Protocol=Video-level2026.05 | 85.6 | — | — | |
| FS-VFMTraining Data=FF++, Evaluation Protocol=Video-level2026.05 | 85.5 | — | — | |
| CNN Forensics2025.11 | 84.9 | — | — | |
| EffortTraining Data=FF++, Evaluation Protocol=Video-level2026.05 | 84.8 | — | — | |
| GenD (DINO)Input=Frame, Backbone=DINOv3 ViT-L/16, Training Dataset=FF++2025.08 | 84.7 | — | — | |
| SPSLScenario=Zero-Day, Train/Test=A/B2023.11 | 84.4 | — | — | |
| OursTraining Dataset=FF++ c23, Evaluation Protocol=Protocol-12024.08 | 84.3 | — | — | |
| EffortTraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 84.3 | — | — | |
| P&PInput=Video, Backbone=CLIP ViT-L/14, Training Dataset=FF++2025.08 | 84.3 | — | — | |
| EffortInput=Frame, Backbone=CLIP ViT-L/14, Training Dataset=FF++2025.08 | 84.3 | — | — | |
| EffortDetector Type=Binary detector2026.05 | 84.2 | — | — | |
| FakeRadarBackbone=Vision Transformer, Input Type=Video2025.12 | 84.1 | — | — | |
| X^2-DFDTraining Dataset=FF++, Evaluation Protocol=Cross-dataset Evaluation, Re-implemented=true2026.05 | 84.1 | — | — | |
| HFRTraining Dataset=FF++ [7]2026.03 | 84.07 | — | — | |
| EffortTraining Dataset=FF++, Evaluation Protocol=Cross-dataset Evaluation, Re-implemented=true2026.05 | 84 | — | — | |
| EffNetB4Scenario=In-Method, Train/Test=A/A2023.11 | 83.5 | — | — | |
| CDFATraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 83 | — | — | |
| OursTraining Dataset=FaceForensics++ [48], Evaluation Protocol=cross-dataset2026.05 | 82.75 | — | — | |
| OursDetector Type=Language detector2026.05 | 82.75 | — | — | |
| DFD-FCGInput=Video, Backbone=CLIP ViT-L/14, Training Dataset=FF++2025.08 | 81.8 | — | — | |
| SPSLScenario=In-Method, Train/Test=B/B2023.11 | 81.7 | — | — | |
| GenD (PE)Input=Frame, Backbone=PEcoreL, Training Dataset=FF++2025.08 | 81.6 | — | — | |
| CLIP Global2025.11 | 81.4 | — | — | |
| UCFScenario=Zero-Day, Train/Test=A/B2023.11 | 81.3 | — | — | |
| UDDTraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 81.2 | — | — | |
| UDDInput=Frame, Backbone=CLIP ViT-B/16, Training Dataset=FF++2025.08 | 81.2 | — | — | |
| GenD-PETraining Data=FF++, Evaluation Protocol=Video-level2026.05 | 81.1 | — | — | |
| BlenDTraining Data=25k ScaleDF (real) + SBI fakes, Evaluation Protocol=Video-level2026.05 | 81 | — | — | |
| RepDFDTraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 80.9 | — | — | |
| VLFFDTraining Dataset=FF++, Evaluation Protocol=Cross-dataset Evaluation, Re-implemented=true2026.05 | 80.9 | — | — | |
| FSFMTraining Data=FF++, Evaluation Protocol=Video-level2026.05 | 80.9 | — | — | |
| DSMTraining Dataset=FF++ [7], Publication Year=20252026.03 | 80.81 | — | — | |
| UCFVenue=ICCV23, Training set (Real)=true, Training set (Fake)=true2025.03 | 80.5 | — | — | |
| UCFBackbone=Xception, Input Type=Frame2025.12 | 80.5 | — | — | |
| LTTDBackbone=Vision Transformer, Input Type=Video2025.12 | 80.4 | — | — | |
| RAEInput=Frame, Backbone=ViT-B/16, Training Dataset=FF++2025.08 | 80.2 | — | — | |
| F3NETScenario=Zero-Day, Train/Test=A/B2023.11 | 79.8 | — | — | |
| HybridTraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 79.6 | — | — | |
| UCLVLMTraining Dataset=FaceForensics++ [48], Evaluation Protocol=cross-dataset2026.05 | 79.12 | — | — | |
| UCLVLMDetector Type=Language detector2026.05 | 79.12 | — | — | |
| SLADDTraining Data=F2F2022.03 | 78.7 | — | — | |
| GradCAM2025.11 | 78.5 | — | — | |
| TALL++Input=Video, Backbone=Swin-B, Training Dataset=FF++2025.08 | 78.5 | — | — | |
| FFDScenario=Zero-Day, Train/Test=A/B2023.11 | 77.9 | — | — | |
| EFFTTraining Dataset=FF++ [7], Publication Year=20252026.03 | 77.65 | — | — | |
| GM-DFTraining Dataset=FF++ [7], Publication Year=20242026.03 | 77.23 | — | — | |
| SLADDTraining Data=DF2022.03 | 77.2 | — | — | |
| SLADDVenues=CVPR 2022, Training Dataset=FF++ c23, Evaluation Protocol=Protocol-12024.08 | 77.2 | — | — | |
| SLADDTraining Dataset=FaceForensics++ (c23), Evaluation Protocol=Cross-dataset2026.04 | 77.2 | — | — | |
| LSDABackbone=EfficientNet, Input Type=Frame2025.12 | 77 | — | — | |
| LSDAInput=Frame, Backbone=EFNB4, Training Dataset=FF++2025.08 | 77 | — | — | |
| ProDetInput=Frame, Backbone=EFNB4, Training Dataset=FF++2025.08 | 77 | — | — | |
| TALLBackbone=Swin Transformer, Input Type=Video2025.12 | 76.8 | — | — | |
| DAIDTraining Dataset=FF++, Evaluation Protocol=Cross-dataset Evaluation, Re-implemented=true2026.05 | 76.8 | — | — | |
| Two-branchTraining Dataset=FaceForensics++, Evaluation Protocol=Cross-dataset generalization2022.01 | 76.7 | — | — | |
| NACOBackbone=Vision Transformer, Input Type=Video2025.12 | 76.7 | — | — | |
| NACOInput=Video, Backbone=ViT-B/16, Training Dataset=FF++2025.08 | 76.7 | — | — | |
| LocalRLVenue=AAAI21, Training set (Real)=true, Training set (Fake)=false2025.03 | 76.53 | — | — | |
| RealForensicsTraining Dataset=FaceForensics++, Evaluation Protocol=Cross-dataset generalization2022.01 | 75.9 | — | — | |
| UCFTraining Dataset=FF++(C23), Evaluation Protocol=Cross-Dataset2023.11 | 75.9 | — | — | |
| SeeABLEVenues=ICCV 2023, Training Dataset=FF++ c23, Evaluation Protocol=Protocol-12024.08 | 75.9 | — | — | |
| SeeABLEBackbone=EfficientNet, Input Type=Frame2025.12 | 75.9 | — | — | |
| RealForensicsBackbone=3D ResNet, Input Type=Video2025.12 | 75.9 | — | — | |
| RealForensicsInput=Video, Backbone=Modified CSN, Training Dataset=FF++2025.08 | 75.9 | — | — | |
| SeeABLEDetector Type=Binary detector2026.05 | 75.9 | — | — |