Long-tail Learning on AWA-LT

Metric: Per-Class Accuracy (higher is better)

LeaderboardDataset

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#	Model↕	Per-Class Accuracy▼	Augmentations	Paper	Date↕	Code
1	DRAGON + Bal'Loss	76.2	No	From Generalized zero-shot learning to long-tail...	2020-04-05	Code
2	DRAGON	74.1	No	From Generalized zero-shot learning to long-tail...	2020-04-05	Code
3	CADA-VAE	73.5	No	-	-	Code
4	LWS	73.4	No	Decoupling Representation and Classifier for Lon...	2019-10-21	Code
5	LDAM	69.1	No	Learning Imbalanced Datasets with Label-Distribu...	2019-06-18	Code

#1DRAGON + Bal'LossSOTA
76.2
Per-Class Accuracy· 2020-04-05
From Generalized zero-shot learning to long-tail with class descriptors Code
#2DRAGON
74.1
Per-Class Accuracy· 2020-04-05
From Generalized zero-shot learning to long-tail with class descriptors Code
#3CADA-VAE
73.5
Per-Class Accuracy
No paperCode
#4LWSSOTA
73.4
Per-Class Accuracy· 2019-10-21
Decoupling Representation and Classifier for Long-Tailed Recognition Code
#5LDAMSOTA
69.1
Per-Class Accuracy· 2019-06-18
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Code