Face Forgery Detection on GenFace AM
64.92AccuracyMFVLR
Evaluation results
| Method | Links | ||
|---|---|---|---|
| MFVLRTraining Set=FS2026.05 | 64.92 | 83.73 | |
| MFCLIPTraining Set=FS2026.05 | 62.58 | 80.38 | |
| MFVLRTraining Set=EFS2026.05 | 60.13 | 80.72 | |
| MFCLIPTraining Set=EFS2026.05 | 58.05 | 78.76 | |
| MSCCNetTraining Set=EFS2026.05 | 57.3 | 75.98 | |
| MSCCNetTraining Set=FS2026.05 | 56.98 | 80.56 | |
| CLIPTraining Set=EFS2026.05 | 56.05 | 64.32 | |
| DD-VQATraining Set=EFS2026.05 | 55.96 | 74.02 | |
| FatFormerTraining Set=EFS2026.05 | 55.89 | 66.9 | |
| VLFFDTraining Set=EFS2026.05 | 55.31 | 73.89 | |
| M2TRTraining Set=FS2026.05 | 55.12 | 79.52 | |
| DD-VQATraining Set=FS2026.05 | 54.79 | 76.05 | |
| ViTTraining Set=EFS2026.05 | 54.69 | 65.86 | |
| VLFFDTraining Set=FS2026.05 | 54.6 | 77.14 | |
| FatFormerTraining Set=FS2026.05 | 53.81 | 65.89 | |
| XceptionTraining Set=FS2026.05 | 53.75 | 75.62 | |
| ViTTraining Set=FS2026.05 | 52.37 | 78.11 | |
| DIRETraining Set=FS2026.05 | 52.13 | 78.32 | |
| FreqNetTraining Set=FS2026.05 | 51.97 | 74.18 | |
| M2TRTraining Set=EFS2026.05 | 50.43 | 64.89 | |
| CLIPTraining Set=FS2026.05 | 50.16 | 62.27 | |
| DIRETraining Set=EFS2026.05 | 50.03 | 76.14 | |
| CViTTraining Set=EFS2026.05 | 50.02 | 63.53 | |
| XceptionTraining Set=EFS2026.05 | 50 | 63.14 | |
| FreqNetTraining Set=EFS2026.05 | 50 | 75.41 | |
| CViTTraining Set=FS2026.05 | 49.98 | 73.75 |