Pets

Benchmarks

Task Name	Dataset Name	SOTA Result
Image Classification	Pets	Accuracy99.75	308
Image Classification	Pets (test)	Accuracy98.22	58
Fine-grained Classification	Pets	Accuracy93.7	53
Image Classification	Pets	Top-1 Accuracy95.4	52
Model Selection	Pets	Weighted Kendall's Tau0.841	36
Image Classification	Pets	Accuracy94.5	33
Image Classification	Pets	Accuracy91.6	30
Image-to-image retrieval	Pets	mAP82.3	30
Fine-grained classification	Pets (test)	Accuracy70.7	29
Multi-view crowd counting	PETS 2009 (test)	MAE3.29	27
Image Classification	Pets	Base Accuracy96.8	27
Multi-Object Tracking	PETS 2009 (S2.L1)	MOTA97.8	26
Classification	Pets	Accuracy93.5	24
Classification	Pets	AURC0.221	23
Clustering	Pets	NMI93.7	21
Feature Inversion	Pets	SSIM52.1	20
Fine-grained classification	Pets	Clean Accuracy88.3	18
Multi-view Crowd Counting	PETS 2009	MAE2.97	15
Fine-Grained Visual Categorization	Pets-37	cACC86.5	15
Backdoor Attack	Pets	CAD-8.2	13
Transferability Estimation	Pets	Weighted Kendall's tau0.792	13
Image Classification	Pets	Error Rate7.746	12
Image Classification	Pets 37	Top-1 Accuracy94.8	11
Image Classification	Pets37	Accuracy93.8	10
Predicting Generalization	Pets PGDL (train test)	CMI5.92	10

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