Image Classification on CIFAR-100-N-LT synthetic (test)
48.98Average Accuracy (%)Dynamic Loss
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| Dynamic LossSelection=Best, Backbone=PreAct ResNet-182022.11 | 48.98 | — | |
| Dynamic LossSelection=Last, Backbone=PreAct ResNet-182022.11 | 48.56 | — | |
| DivideMix + Balanced-SoftmaxSelection=Best, Backbone=PreAct ResNet-182022.11 | 46.92 | — | |
| DivideMix + Balanced-SoftmaxSelection=Last, Backbone=PreAct ResNet-182022.11 | 46.11 | — | |
| HARSelection=Best, Backbone=PreAct ResNet-182022.11 | 43.98 | — | |
| HARSelection=Last, Backbone=PreAct ResNet-182022.11 | 42.77 | — | |
| Balanced-SoftmaxSelection=Best, Backbone=PreAct ResNet-182022.11 | 41.82 | — | |
| DivideMixSelection=Best, Backbone=PreAct ResNet-182022.11 | 41.75 | — | |
| Balanced-SoftmaxSelection=Last, Backbone=PreAct ResNet-182022.11 | 41.3 | — | |
| DivideMixSelection=Last, Backbone=PreAct ResNet-182022.11 | 41.15 | — | |
| ELR+Selection=Best, Backbone=PreAct ResNet-182022.11 | 36.2 | — | |
| MOIT+Selection=Best, Backbone=PreAct ResNet-182022.11 | 35.02 | — | |
| ELR+Selection=Last, Backbone=PreAct ResNet-182022.11 | 34.96 | — | |
| CurveNetSelection=Best, Backbone=PreAct ResNet-182022.11 | 32.72 | — | |
| FaMUSSelection=Best, Backbone=PreAct ResNet-182022.11 | 30.81 | — | |
| FaMUSSelection=Last, Backbone=PreAct ResNet-182022.11 | 30.72 | — | |
| CurveNetSelection=Last, Backbone=PreAct ResNet-182022.11 | 29.83 | — | |
| Cross EntropySelection=Best, Backbone=PreAct ResNet-182022.11 | 26.67 | — | |
| Cross EntropySelection=Last, Backbone=PreAct ResNet-182022.11 | 25.41 | — | |
| Dynamic LossImbalance Ratio=10, Noise Rate=0.1, Selection=Best, Backbone=PreAct ResNet-182022.11 | — | 59.52 | |
| Dynamic LossImbalance Ratio=10, Noise Rate=0.5, Selection=Best, Backbone=PreAct ResNet-182022.11 | — | 51.26 | |
| Dynamic LossImbalance Ratio=100, Noise Rate=0.1, Selection=Best, Backbone=PreAct ResNet-182022.11 | — | 47.55 | |
| Dynamic LossImbalance Ratio=100, Noise Rate=0.5, Selection=Best, Backbone=PreAct ResNet-182022.11 | — | 34.3 |