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Benchmarks
Image Classification on FaceScrub (val)
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85.12
Accuracy
Bottleneck
78.9424
80.5462
82.15
83.7538
Mar 1, 2025
Accuracy
Updated 3mo ago
Evaluation Results
Method
Method
Links
Accuracy
Bottleneck
2025.03
85.12
Bottleneck+CEM
integration=CEM
2025.03
85
DistCorr+CEM
integration=CEM
2025.03
83.78
DistCorr
2025.03
83.42
Noise_Nopeek
2025.03
82.06
Noise_Nopeek+CEM
integration=CEM
2025.03
81.96
Average w/ CEM
2025.03
81.38
Average w/o CEM
2025.03
81.26
Noise_ARL+CEM
integration=CEM
2025.03
80.33
Noise_ARL
2025.03
80.14
PATROL+CEM
integration=CEM
2025.03
79.88
ResSFL
2025.03
79.6
ResSFL+CEM
integration=CEM
2025.03
79.54
Dropout
2025.03
79.3
Dropout+CEM
integration=CEM
2025.03
79.19
PATROL
2025.03
79.18
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