Image Classification on ImageNet

Metric: Accuracy (%) (higher is better)

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#	Model↕	Accuracy (%)▼	Extra Data	Paper	Date↕	Code
1	TURTLE (CLIP + DINOv2)	72.9	Yes	Let Go of Your Labels with Unsupervised Transfer	2024-06-11	Code
2	I-Con (Dino ViT-L)	67.52	No	-	-	-
3	iBOT (ViT-S/16)	43.4	No	iBOT: Image BERT Pre-Training with Online Tokeni...	2021-11-15	Code
4	Self-Classifier (ResNet-50)	41.1	No	Self-Supervised Classification Network	2021-03-19	Code
5	TWIST (ResNet-50)	40.6	No	Self-Supervised Learning by Estimating Twin Clas...	2021-10-14	Code
6	SCAN (ResNet-50)	39.9	No	SCAN: Learning to Classify Images without Labels	2020-05-25	Code
7	DeepDPM (nonparametric)	25	No	DeepDPM: Deep Clustering With an Unknown Number ...	2022-03-27	Code

#1TURTLE (CLIP + DINOv2)SOTA
72.9
Accuracy (%)· Extra Data· 2024-06-11
Let Go of Your Labels with Unsupervised Transfer Code
#2I-Con (Dino ViT-L)
67.52
Accuracy (%)
No paper
#3iBOT (ViT-S/16)SOTA
43.4
Accuracy (%)· 2021-11-15
iBOT: Image BERT Pre-Training with Online Tokenizer Code
#4Self-Classifier (ResNet-50)SOTA
41.1
Accuracy (%)· 2021-03-19
Self-Supervised Classification Network Code
#5TWIST (ResNet-50)
40.6
Accuracy (%)· 2021-10-14
Self-Supervised Learning by Estimating Twin Class Distributions Code
#6SCAN (ResNet-50)SOTA
39.9
Accuracy (%)· 2020-05-25
SCAN: Learning to Classify Images without Labels Code
#7DeepDPM (nonparametric)
25
Accuracy (%)· 2022-03-27
DeepDPM: Deep Clustering With an Unknown Number of Clusters Code