Incremental Learning on ImageNet100 - 10 steps

Metric: Final Accuracy (higher is better)

LeaderboardDataset

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#	Model↕	Final Accuracy▼	Augmentations	Paper	Date↕	Code
1	DyTox	69.1	No	DyTox: Transformers for Continual Learning with ...	2021-11-22	Code
2	TCIL	67.34	No	Resolving Task Confusion in Dynamic Expansion Ar...	2022-12-29	Code
3	TCIL-Lite	67.3	No	Resolving Task Confusion in Dynamic Expansion Ar...	2022-12-29	Code
4	DER w/o Pruning	66.7	No	DER: Dynamically Expandable Representation for C...	2021-03-31	Code
5	DER	66.07	No	DER: Dynamically Expandable Representation for C...	2021-03-31	Code

#1DyToxSOTA
69.1
Final Accuracy· 2021-11-22
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion Code
#2TCIL
67.34
Final Accuracy· 2022-12-29
Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning Code
#3TCIL-Lite
67.3
Final Accuracy· 2022-12-29
Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning Code
#4DER w/o PruningSOTA
66.7
Final Accuracy· 2021-03-31
DER: Dynamically Expandable Representation for Class Incremental Learning Code
#5DER
66.07
Final Accuracy· 2021-03-31
DER: Dynamically Expandable Representation for Class Incremental Learning Code