Incremental Learning on ImageNet - 10 steps

Metric: Final Accuracy (higher is better)

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#	Model↕	Final Accuracy▼	Augmentations	Paper	Date↕	Code
1	DyTox	63.34	No	DyTox: Transformers for Continual Learning with ...	2021-11-22	Code
2	DER w/o Pruning	60.16	No	DER: Dynamically Expandable Representation for C...	2021-03-31	Code
3	DER	58.62	No	DER: Dynamically Expandable Representation for C...	2021-03-31	Code
4	WA	55.6	No	Maintaining Discrimination and Fairness in Class...	2019-11-16	Code
5	iCaRL	22.7	No	iCaRL: Incremental Classifier and Representation...	2016-11-23	Code

#1DyToxSOTA
63.34
Final Accuracy· 2021-11-22
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion Code
#2DER w/o PruningSOTA
60.16
Final Accuracy· 2021-03-31
DER: Dynamically Expandable Representation for Class Incremental Learning Code
#3DER
58.62
Final Accuracy· 2021-03-31
DER: Dynamically Expandable Representation for Class Incremental Learning Code
#4WASOTA
55.6
Final Accuracy· 2019-11-16
Maintaining Discrimination and Fairness in Class Incremental Learning Code
#5iCaRLSOTA
22.7
Final Accuracy· 2016-11-23
iCaRL: Incremental Classifier and Representation Learning Code