Fine-grained Image Classification

Benchmarks

Dataset Name	SOTA Method	Metric
CUB200 2011 (test)	HERBS	Accuracy93.1	536	3d ago
Stanford Cars (test)	PMAL	Accuracy97.3	348	3d ago
CUB-200 2011	CSQA-Net	Accuracy92.6	222	3d ago
Stanford Cars	CAP	Accuracy95.7	206	2d ago
Stanford Dogs (test)	SR-GNN	Accuracy97.3	117	3d ago
CUB-200 2011 (test)	IVPT	Consistency Score75.3	65	3d ago
Oxford Flowers	MCLoss	Accuracy97.7	49	3d ago
CUB-200 (test)	SR-GNN	Accuracy91.9	45	3d ago
Aircraft (test)	DivideMix + SNSCL	Best Accuracy84.17	40	3d ago
FGVC-Aircraft	PMG	Accuracy (All)93.4	39	3d ago
DTD (novel classes)	TCPT	ECE3.3	36	2d ago
FGVCAircraft (novel classes)	ZS-Norm	ECE3.79	36	2d ago
UCF101	Fair Context Learning (FCL)	Accuracy68.52	34	2d ago
CUB-200	VAN	Accuracy (All)91.3	32	3d ago
Oxford-IIIT Pets	CAP	Accuracy97.3	29	2d ago
UCF101 novel classes	TCPT	Expected Calibration Error1.89	28	2d ago
Flowers102 (novel classes)	TCPT	ECE3.51	28	2d ago
StanfordCars (novel classes)	CoCoOp	ECE1.88	28	2d ago
OxfordPets (novel classes)	TCPT	ECE1.19	28	2d ago
Caltech101 (novel classes)	TCPT	ECE1.03	28	2d ago
StanfordCars base classes	Temp. Scal.	Accuracy78.65	27	2d ago
Flowers102 base-to-new	PromptSRC + DePT	Base Accuracy98.4	26	3d ago
Oxford Flowers (test)	ARC*	Top-1 Accuracy99.7	24	3d ago
Aircrafts 1.0 (val)	MPN-COV + SEB	Accuracy93.5	24	3d ago
Birds 1.0 (val)	MPN-COV + SEB	Accuracy88.2	24	3d ago

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