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Image Classification on CIFAR-LT-100 (test)

42.15Top-1 ErrorMetaSAug with CE loss
41.171247.778154.38560.9919Aug 5, 2022
Updated 8mo ago

Evaluation results

MethodLinks
MetaSAug with CE lossBackbone=ResNet-32, Imbalance Factor=202022.0842.15
MetaSAug with focal lossBackbone=ResNet-32, Imbalance Factor=202022.0842.41
MetaSAug with LDAM lossBackbone=ResNet-32, Imbalance Factor=202022.0842.47
Optimal Transport Re-weighting (Weight Vector)Backbone=ResNet-32, Imbalance Factor=202022.0842.85
Meta-class-weight with focal lossBackbone=ResNet-32, Imbalance Factor=202022.0844.27
Meta-class-weight with CE lossBackbone=ResNet-32, Imbalance Factor=202022.0844.38
IB + Focal lossBackbone=ResNet-32, Imbalance Factor=202022.0845.47
IBBackbone=ResNet-32, Imbalance Factor=202022.0846.43
IB + CBBackbone=ResNet-32, Imbalance Factor=202022.0846.58
Meta-weight netBackbone=ResNet-32, Imbalance Factor=202022.0846.96
LDAM-DRWBackbone=ResNet-32, Imbalance Factor=202022.0847.01
CB, Focal lossBackbone=ResNet-32, Imbalance Factor=202022.0847.41
Optimal Transport Re-weighting (Weight Vector)Backbone=ResNet-32, Imbalance Factor=502022.0847.5
Meta-class-weight with LDAM lossBackbone=ResNet-32, Imbalance Factor=202022.0847.62
MetaSAug with LDAM lossBackbone=ResNet-32, Imbalance Factor=502022.0847.73
Focal lossBackbone=ResNet-32, Imbalance Factor=202022.0848.05
CB, CE lossBackbone=ResNet-32, Imbalance Factor=202022.0848.06
MetaSAug with CE lossBackbone=ResNet-32, Imbalance Factor=502022.0848.1
L2RWBackbone=ResNet-32, Imbalance Factor=202022.0848.36
MetaSAug with focal lossBackbone=ResNet-32, Imbalance Factor=502022.0848.38
LDAM lossBackbone=ResNet-32, Imbalance Factor=202022.0848.41
CE lossBackbone=ResNet-32, Imbalance Factor=202022.0848.94
Meta-class-weight with focal lossBackbone=ResNet-32, Imbalance Factor=502022.0849.92
Meta-class-weight with LDAM lossBackbone=ResNet-32, Imbalance Factor=502022.0850.84
IBBackbone=ResNet-32, Imbalance Factor=502022.0851.07
IB + Focal lossBackbone=ResNet-32, Imbalance Factor=502022.0851.08
IB + CBBackbone=ResNet-32, Imbalance Factor=502022.0851.2
Optimal Transport Re-weighting (Weight Vector)Backbone=ResNet-32, Imbalance Factor=1002022.0851.46
Meta-class-weight with CE lossBackbone=ResNet-32, Imbalance Factor=502022.0851.47
MetaSAug with LDAM lossBackbone=ResNet-32, Imbalance Factor=1002022.0851.99
LDAM-DRWBackbone=ResNet-32, Imbalance Factor=502022.0852.03
BBNBackbone=ResNet-32, Imbalance Factor=502022.0852.98
MetaSAug with CE lossBackbone=ResNet-32, Imbalance Factor=1002022.0853.13
LDAM lossBackbone=ResNet-32, Imbalance Factor=502022.0853.84
MetaSAug with focal lossBackbone=ResNet-32, Imbalance Factor=1002022.0854.11
Meta-weight netBackbone=ResNet-32, Imbalance Factor=502022.0854.34
IBBackbone=ResNet-32, Imbalance Factor=1002022.0854.61
IB + CBBackbone=ResNet-32, Imbalance Factor=1002022.0854.73
CB, Focal lossBackbone=ResNet-32, Imbalance Factor=502022.0854.79
Optimal Transport Re-weighting (Weight Vector)Backbone=ResNet-32, Imbalance Factor=2002022.0854.97
IB + Focal lossBackbone=ResNet-32, Imbalance Factor=1002022.0855.04
CB, CE lossBackbone=ResNet-32, Imbalance Factor=502022.0855.21
Meta-class-weight with focal lossBackbone=ResNet-32, Imbalance Factor=1002022.0855.3
L2RWBackbone=ResNet-32, Imbalance Factor=502022.0855.56
Focal lossBackbone=ResNet-32, Imbalance Factor=502022.0855.68
Meta-class-weight with LDAM lossBackbone=ResNet-32, Imbalance Factor=1002022.0855.92
CE lossBackbone=ResNet-32, Imbalance Factor=502022.0855.98
Meta-class-weight with CE lossBackbone=ResNet-32, Imbalance Factor=1002022.0856.65
MetaSAug with LDAM lossBackbone=ResNet-32, Imbalance Factor=2002022.0856.91
LDAM-DRWBackbone=ResNet-32, Imbalance Factor=1002022.0857.11
BBNBackbone=ResNet-32, Imbalance Factor=1002022.0857.44
Meta-weight netBackbone=ResNet-32, Imbalance Factor=1002022.0858.39
LDAM lossBackbone=ResNet-32, Imbalance Factor=1002022.0859.4
IB + Focal lossBackbone=ResNet-32, Imbalance Factor=2002022.0859.61
L2RWBackbone=ResNet-32, Imbalance Factor=1002022.0859.77
MetaSAug with focal lossBackbone=ResNet-32, Imbalance Factor=2002022.0859.78
MetaSAug with CE lossBackbone=ResNet-32, Imbalance Factor=2002022.0860.06
IB + CBBackbone=ResNet-32, Imbalance Factor=2002022.0860.31
IBBackbone=ResNet-32, Imbalance Factor=2002022.0860.34
CB, Focal lossBackbone=ResNet-32, Imbalance Factor=1002022.0860.4
Meta-class-weight with LDAM lossBackbone=ResNet-32, Imbalance Factor=2002022.0860.47
Meta-class-weight with focal lossBackbone=ResNet-32, Imbalance Factor=2002022.0860.66
Meta-class-weight with CE lossBackbone=ResNet-32, Imbalance Factor=2002022.0860.69
CB, CE lossBackbone=ResNet-32, Imbalance Factor=1002022.0861.23
CE lossBackbone=ResNet-32, Imbalance Factor=1002022.0861.54
LDAM-DRWBackbone=ResNet-32, Imbalance Factor=2002022.0861.55
Focal lossBackbone=ResNet-32, Imbalance Factor=1002022.0861.59
Meta-weight netBackbone=ResNet-32, Imbalance Factor=2002022.0863.38
LDAM lossBackbone=ResNet-32, Imbalance Factor=2002022.0863.47
CB, Focal lossBackbone=ResNet-32, Imbalance Factor=2002022.0863.77
Focal lossBackbone=ResNet-32, Imbalance Factor=2002022.0864.38
CB, CE lossBackbone=ResNet-32, Imbalance Factor=2002022.0864.44
CE lossBackbone=ResNet-32, Imbalance Factor=2002022.0865.3
L2RWBackbone=ResNet-32, Imbalance Factor=2002022.0866.62