Incremental Learning on Tiny-ImageNet 5 task
55.25Average Incremental AccuracyUpper bound
Evaluation Results
| Method | Links | |
|---|---|---|
| Upper boundModel Inversion=false, Backbone=ResNet-32, Number of runs=52026.05 | 55.25 | |
| Upper boundModel inversion=false, Backbone=ResNet-32, Number of runs=52026.05 | 55.25 | |
| REMIXModel Inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 38.64 | |
| REMIXModel inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 38.64 | |
| PMIModel Inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 37.9 | |
| PMIModel inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 37.9 | |
| PMI w/o CFSModel Inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 37.65 | |
| PMI w/o CFSModel inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 37.65 | |
| DCMIModel inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 35.78 | |
| R-DFCILModel Inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 35.33 | |
| R-DFCILModel inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 35.33 | |
| PRAKAModel inversion=false, Backbone=ResNet-32, Number of runs=52026.05 | 31.69 | |
| ABDModel Inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 30.83 | |
| ABDModel inversion=true, Backbone=ResNet-32, Number of runs=52026.05 | 30.83 | |
| SSREModel inversion=false, Backbone=ResNet-32, Number of runs=52026.05 | 26.22 |