Incremental Learning On Cifar 100 50 Classes 1
Metrics
Average Incremental Accuracy
Results
Performance results of various models on this benchmark
Model Name | Average Incremental Accuracy | Paper Title | Repository |
|---|---|---|---|
| FOSTER | 63.83 | FOSTER: Feature Boosting and Compression for Class-Incremental Learning | |
| RMM (Modified ResNet-32) | 66.21 | RMM: Reinforced Memory Management for Class-Incremental Learning | |
| BiC | 48.96 | Large Scale Incremental Learning | |
| PODNet | 60.72 | PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning | |
| D3Former | 68.68 | D3Former: Debiased Dual Distilled Transformer for Incremental Learning |
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