Image Classification on Red MiniImageNet 80% label noise

Metric: Accuracy (higher is better)

LeaderboardDataset

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	NCR (ResNet-18)	51.2	No	Learning with Neighbor Consistency for Noisy Lab...	2022-02-04	Code
2	InstanceGM-SS	44.03	No	Instance-Dependent Noisy Label Learning via Grap...	2022-09-02	Code
3	PropMix	43.42	No	PropMix: Hard Sample Filtering and Proportional ...	2021-10-22	Code
4	InstanceGM	39.62	No	Instance-Dependent Noisy Label Learning via Grap...	2022-09-02	Code
5	FaMUS	35.5	No	Faster Meta Update Strategy for Noise-Robust Dee...	2021-04-30	Code

#1NCR (ResNet-18)SOTA
51.2
Accuracy· 2022-02-04
Learning with Neighbor Consistency for Noisy Labels Code
#2InstanceGM-SS
44.03
Accuracy· 2022-09-02
Instance-Dependent Noisy Label Learning via Graphical Modelling Code
#3PropMixSOTA
43.42
Accuracy· 2021-10-22
PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels Code
#4InstanceGM
39.62
Accuracy· 2022-09-02
Instance-Dependent Noisy Label Learning via Graphical Modelling Code
#5FaMUSSOTA
35.5
Accuracy· 2021-04-30
Faster Meta Update Strategy for Noise-Robust Deep Learning Code