Fine-grained Image Classification

Benchmarks

Dataset Name	SOTA Method	Metric
CUB200 2011 (test)	HERBS	Accuracy93.1	543	10d ago
Stanford Cars (test)	PMAL	Accuracy97.3	348	1mo ago
CUB-200 2011	CSQA-Net	Accuracy92.6	300	22d ago
Stanford Cars	CAP	Accuracy95.7	284	22d ago
Stanford Dogs (test)	SR-GNN	Accuracy97.3	124	10d ago
CUB-200 2011 (test)	IVPT	Consistency Score75.3	65	1mo ago
FGVC-Aircraft	PMG	Accuracy (All)93.4	50	11d ago
Oxford Flowers	MCLoss	Accuracy97.7	49	1mo ago
CUB-200 (test)	SR-GNN	Accuracy91.9	45	1mo ago
Aircraft (test)	DivideMix + SNSCL	Best Accuracy84.17	40	1mo ago
DTD (novel classes)	TCPT	ECE3.3	36	1mo ago
FGVCAircraft (novel classes)	ZS-Norm	ECE3.79	36	1mo ago
CUB	MPO	Top-1 Acc78.6	35	1mo ago
UCF101	Fair Context Learning (FCL)	Accuracy68.52	34	1mo ago
CUB-200	VAN	Accuracy (All)91.3	32	1mo ago
Oxford-IIIT Pets	CAP	Accuracy97.3	29	1mo ago
UCF101 novel classes	TCPT	Expected Calibration Error1.89	28	1mo ago
Flowers102 (novel classes)	TCPT	ECE3.51	28	1mo ago
StanfordCars (novel classes)	CoCoOp	ECE1.88	28	1mo ago
OxfordPets (novel classes)	TCPT	ECE1.19	28	1mo ago
Caltech101 (novel classes)	TCPT	ECE1.03	28	1mo ago
Flowers102 base-to-new	PromptSRC + DePT	Base Accuracy98.4	28	1mo ago
StanfordCars base classes	Temp. Scal.	Accuracy78.65	27	1mo ago
Oxford Flowers (test)	ARC*	Top-1 Accuracy99.7	24	1mo ago
Aircrafts 1.0 (val)	MPN-COV + SEB	Accuracy93.5	24	1mo ago

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