Model Inversion Attack on VGGFace2
93.88Top-1 AccPPA
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| PPADefense=BiDO, Hyperparameters=0.006, 0.06, Target Model Accuracy=92.20, Target Backbone=MobileNetV22025.03 | 93.88 | 95.92 | — | — | |
| PPADefense=MID, Hyperparameters=0.005, Target Model Accuracy=91.31, Target Backbone=MobileNetV22025.03 | 93.88 | 100 | — | — | |
| PPADefense=LS, Hyperparameters=-0.001, Target Model Accuracy=92.40, Target Backbone=MobileNetV22025.03 | 87.76 | 95.92 | — | — | |
| PPADefense=MID, Hyperparameters=0.005, Target Model Accuracy=89.50, Target Backbone=Swin Transformer2025.03 | 83.67 | 93.87 | — | — | |
| PPADefense=TL, Hyperparameters=Block 4, Target Model Accuracy=93.82, Target Backbone=MobileNetV22025.03 | 81.63 | 95.92 | — | — | |
| SMILE (InceptionV1*)Target Model=ResNet50, Image Prior=FFHQ, Surrogate Model=InceptionV1, Initialization=Pre-trained2025.03 | 68.71 | 93.2 | 262.56 | 237.75 | |
| PPADefense=LS, Hyperparameters=-0.0005, Target Model Accuracy=92.48, Target Backbone=Swin Transformer2025.03 | 65.31 | 77.55 | — | — | |
| Mirror-wTarget Model=ResNet50, Image Prior=CelebA2025.03 | 63.27 | 79.59 | 313.33 | 280.97 | |
| PPADefense=BiDO, Hyperparameters=0.03, 0.3, Target Model Accuracy=91.57, Target Backbone=MobileNetV22025.03 | 55.11 | 75.51 | — | — | |
| SMILE (InceptionV1*)Target Model=ResNet50, Image Prior=CelebA, Surrogate Model=InceptionV1, Initialization=Pre-trained2025.03 | 44.22 | 61.9 | 339.16 | 306.98 | |
| PPADefense=TL, Hyperparameters=Block 3, Target Model Accuracy=91.98, Target Backbone=Swin Transformer2025.03 | 34.69 | 59.18 | — | — | |
| SMILEDefense=LS, Hyperparameters=-0.001, Target Model Accuracy=92.40, Target Backbone=MobileNetV22025.03 | 30.61 | 38.78 | — | — | |
| SMILEDefense=LS, Hyperparameters=-0.0005, Target Model Accuracy=92.48, Target Backbone=Swin Transformer2025.03 | 24.49 | 34.69 | — | — | |
| SMILEDefense=BiDO, Hyperparameters=0.03, 0.3, Target Model Accuracy=91.57, Target Backbone=MobileNetV22025.03 | 22.49 | 36.73 | — | — | |
| SMILEDefense=BiDO, Hyperparameters=0.006, 0.06, Target Model Accuracy=92.20, Target Backbone=MobileNetV22025.03 | 22.45 | 40.82 | — | — | |
| SMILEDefense=TL, Hyperparameters=Block 4, Target Model Accuracy=93.82, Target Backbone=MobileNetV22025.03 | 20.41 | 36.73 | — | — | |
| RLBMIDefense=MID, Hyperparameters=0.005, Target Model Accuracy=89.50, Target Backbone=Swin Transformer2025.03 | 18.36 | 24.48 | — | — | |
| SMILEDefense=MID, Hyperparameters=0.005, Target Model Accuracy=91.31, Target Backbone=MobileNetV22025.03 | 14.29 | 26.53 | — | — | |
| RLBMIDefense=TL, Hyperparameters=Block 4, Target Model Accuracy=93.82, Target Backbone=MobileNetV22025.03 | 14.28 | 16.32 | — | — | |
| Mirror-bDefense=BiDO, Hyperparameters=0.006, 0.06, Target Model Accuracy=92.20, Target Backbone=MobileNetV22025.03 | 12.24 | 16.33 | — | — | |
| Mirror-bDefense=LS, Hyperparameters=-0.0005, Target Model Accuracy=92.48, Target Backbone=Swin Transformer2025.03 | 10.2 | 14.29 | — | — | |
| SMILEDefense=TL, Hyperparameters=Block 3, Target Model Accuracy=91.98, Target Backbone=Swin Transformer2025.03 | 10.2 | 24.49 | — | — | |
| RLBMIDefense=BiDO, Hyperparameters=0.006, 0.06, Target Model Accuracy=92.20, Target Backbone=MobileNetV22025.03 | 8.16 | 16.32 | — | — | |
| RLBMIDefense=BiDO, Hyperparameters=0.03, 0.3, Target Model Accuracy=91.57, Target Backbone=MobileNetV22025.03 | 8.16 | 22.44 | — | — | |
| Mirror-bDefense=MID, Hyperparameters=0.005, Target Model Accuracy=91.31, Target Backbone=MobileNetV22025.03 | 8.16 | 24.49 | — | — | |
| Mirror-bDefense=LS, Hyperparameters=-0.001, Target Model Accuracy=92.40, Target Backbone=MobileNetV22025.03 | 8.16 | 10.2 | — | — | |
| RLBMIDefense=LS, Hyperparameters=-0.0005, Target Model Accuracy=92.48, Target Backbone=Swin Transformer2025.03 | 8.16 | 12.24 | — | — | |
| Mirror-bDefense=BiDO, Hyperparameters=0.03, 0.3, Target Model Accuracy=91.57, Target Backbone=MobileNetV22025.03 | 6.12 | 14.29 | — | — | |
| RLBMIDefense=MID, Hyperparameters=0.005, Target Model Accuracy=91.31, Target Backbone=MobileNetV22025.03 | 6.12 | 22.44 | — | — | |
| SMILEDefense=MID, Hyperparameters=0.005, Target Model Accuracy=89.50, Target Backbone=Swin Transformer2025.03 | 6.12 | 10.2 | — | — | |
| Mirror-bDefense=TL, Hyperparameters=Block 4, Target Model Accuracy=93.82, Target Backbone=MobileNetV22025.03 | 6.12 | 10.2 | — | — | |
| Mirror-bDefense=MID, Hyperparameters=0.005, Target Model Accuracy=89.50, Target Backbone=Swin Transformer2025.03 | 4.08 | 4.08 | — | — | |
| RLBMIDefense=LS, Hyperparameters=-0.001, Target Model Accuracy=92.40, Target Backbone=MobileNetV22025.03 | 4.08 | 14.28 | — | — | |
| RLBMIDefense=TL, Hyperparameters=Block 3, Target Model Accuracy=91.98, Target Backbone=Swin Transformer2025.03 | 4.08 | 6.12 | — | — | |
| Mirror-bDefense=TL, Hyperparameters=Block 3, Target Model Accuracy=91.98, Target Backbone=Swin Transformer2025.03 | 2.04 | 6.12 | — | — |