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Face Retrieval on CFP-FP
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91
mAP
Original
55.952
65.051
74.15
83.249
Dec 15, 2025
mAP
Rank-1 Accuracy
Updated 4d ago
Evaluation Results
Method
Method
Links
mAP
Rank-1 Accuracy
Original
Backbone=IResNet-50
2025.12
91
97.5
Contrastive Unlearning
lambda_retain=0
2025.12
91
97.57
Random Labeling
lambda_retain=1
2025.12
90
97.33
Gradient Ascent
learning rate=1e-5
2025.12
89.4
97.2
Dispersion Loss
learning rate=1e-4, ma...
2025.12
89.2
97.3
Hard Dispersion Loss
learning rate=1e-4, ma...
2025.12
89.2
97.27
Boundary Shrink
learning rate=1e-5
2025.12
88.47
97.13
Lipschitz Unlearning
lambda_retain=0.05
2025.12
87.67
97.07
Original
batch size=160
2025.12
70.1
74.1
Dispersion Loss
batch size=160
2025.12
63.23
72.17
Hard Dispersion Loss
batch size=160
2025.12
57.3
69.7
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