Few-Shot Image Classification on ImageNet - 5-shot

Metric: Top 1 Accuracy (higher is better)

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#	Model↕	Top 1 Accuracy▼	Extra Data	Paper	Date↕	Code
1	ViT-MoE-15B (Every-2)	82.78	No	Scaling Vision with Sparse Mixture of Experts	2021-06-10	Code
2	MAWS (ViT-6.5B)	82.6	Yes	The effectiveness of MAE pre-pretraining for bil...	2023-03-23	Code
3	MAWS (ViT-2B)	81.5	Yes	The effectiveness of MAE pre-pretraining for bil...	2023-03-23	Code
4	MAWS (ViT-H)	79.8	Yes	The effectiveness of MAE pre-pretraining for bil...	2023-03-23	Code
5	V-MoE-H/14 (Every-2)	78.21	No	Scaling Vision with Sparse Mixture of Experts	2021-06-10	Code
6	V-MoE-H/14 (Last-5)	78.08	No	Scaling Vision with Sparse Mixture of Experts	2021-06-10	Code
7	V-MoE-L/16 (Every-2)	77.1	No	Scaling Vision with Sparse Mixture of Experts	2021-06-10	Code
8	VIT-H/14	76.95	No	Scaling Vision with Sparse Mixture of Experts	2021-06-10	Code

#1ViT-MoE-15B (Every-2)SOTA
82.78
Top 1 Accuracy· 2021-06-10
Scaling Vision with Sparse Mixture of Experts Code
#2MAWS (ViT-6.5B)
82.6
Top 1 Accuracy· Extra Data· 2023-03-23
The effectiveness of MAE pre-pretraining for billion-scale pretraining Code
#3MAWS (ViT-2B)
81.5
Top 1 Accuracy· Extra Data· 2023-03-23
The effectiveness of MAE pre-pretraining for billion-scale pretraining Code
#4MAWS (ViT-H)
79.8
Top 1 Accuracy· Extra Data· 2023-03-23
The effectiveness of MAE pre-pretraining for billion-scale pretraining Code
#5V-MoE-H/14 (Every-2)
78.21
Top 1 Accuracy· 2021-06-10
Scaling Vision with Sparse Mixture of Experts Code
#6V-MoE-H/14 (Last-5)
78.08
Top 1 Accuracy· 2021-06-10
Scaling Vision with Sparse Mixture of Experts Code
#7V-MoE-L/16 (Every-2)
77.1
Top 1 Accuracy· 2021-06-10
Scaling Vision with Sparse Mixture of Experts Code
#8VIT-H/14
76.95
Top 1 Accuracy· 2021-06-10
Scaling Vision with Sparse Mixture of Experts Code