Pets

Benchmarks

Task Name	Dataset Name	SOTA Result
Image Classification	Pets	Accuracy99.75	204
Model Selection	Pets	Weighted Kendall's Tau0.841	36
Image Classification	Pets (test)	Accuracy98.22	36
Image Classification	Pets	Accuracy94.5	33
Image Classification	Pets	Top-1 Accuracy95.4	29
Multi-view crowd counting	PETS 2009 (test)	MAE3.29	27
Multi-Object Tracking	PETS 2009 (S2.L1)	MOTA97.8	26
Classification	Pets	AURC0.221	23
Fine-grained Classification	Pets	Accuracy88.25	22
Classification	Pets	Accuracy93.5	19
Fine-grained classification	Pets	Clean Accuracy88.3	18
Multi-view Crowd Counting	PETS 2009	MAE2.97	15
Backdoor Attack	Pets	CAD-8.2	13
Transferability Estimation	Pets	Weighted Kendall's tau0.792	13
Image Classification	Pets	Error Rate7.746	12
Fine-Grained Visual Categorization	Pets-37	Accuracy92.2	10
Predicting Generalization	Pets PGDL (train test)	CMI5.92	10
Image Classification	Pets original (test)	Accuracy94.5	10
Fine-grained classification	Pets	Mean per Class Accuracy93.1	9
Object Detection	Pets	Mean Per-Class Accuracy95.15	8
Image Classification	Pets	Linear Accuracy0.809	8
Image Classification	Pets	ACE0.005	5
Image Classification	PETS	Accuracy0.952	4
Clustering	Pets	NMI84.9	4
Image Classification	Pets	SCE0.68	4

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