Image Classification on Red MiniImageNet 40% label noise

Metric: Accuracy (higher is better)

LeaderboardDataset

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	NCR (ResNet-18)	64.6	No	Learning with Neighbor Consistency for Noisy Lab...	2022-02-04	Code
2	InstanceGM-SS	56.37	No	Instance-Dependent Noisy Label Learning via Grap...	2022-09-02	Code
3	PropMix	56.22	No	PropMix: Hard Sample Filtering and Proportional ...	2021-10-22	Code
4	InstanceGM	52.24	No	Instance-Dependent Noisy Label Learning via Grap...	2022-09-02	Code
5	FaMUS	48.06	No	Faster Meta Update Strategy for Noise-Robust Dee...	2021-04-30	Code

#1NCR (ResNet-18)SOTA
64.6
Accuracy· 2022-02-04
Learning with Neighbor Consistency for Noisy Labels Code
#2InstanceGM-SS
56.37
Accuracy· 2022-09-02
Instance-Dependent Noisy Label Learning via Graphical Modelling Code
#3PropMixSOTA
56.22
Accuracy· 2021-10-22
PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels Code
#4InstanceGM
52.24
Accuracy· 2022-09-02
Instance-Dependent Noisy Label Learning via Graphical Modelling Code
#5FaMUSSOTA
48.06
Accuracy· 2021-04-30
Faster Meta Update Strategy for Noise-Robust Deep Learning Code