Fine-grained 5-way Classification on Stanford Dogs benchmark leaderboard · SOTA2 Research

Fine-grained 5-way Classification on Stanford Dogs

80.931-shot AccARF-SFR-Net-Snapshot

Evaluation Results

Method	Links
ARF-SFR-Net-Snapshot2026.04		80.93	90.68
ARF-SFR-Net2026.04		78.65	90.2
C2-Net2026.04		77.72	89.59
BDFRNet2026.04		77.4	88.41
FRN2026.04		76.76	88.74
FRN+TDM+BiFI-TDM2026.04		76.72	88.96
SUITED2026.04		76.55	88.86
SRNet2026.04		76.54	88.52
MFSI-Net2026.04		76.35	88.17
AIS2026.04		76.32	88.25
FRN+TDM2026.04		75.98	88.7
ATR-Net2026.04		75.68	87.77
ARF-SFR-Net-Snapshot2026.04		75.45	88.87
DeepBDC2026.04		73.57	86.61
ARF-SFR-Net2026.04		72.26	86.68
C2-Net2026.04		69.81	84.39
BSFANet2026.04		69.58	82.59
SUITED2026.04		68.67	82.24
TST_MFL2026.04		67.84	81.72
HelixFormer2026.04		65.92	80.65
BDFRNet2026.04		64.66	81.27
AIS2026.04		63.13	78.34
FRN+TDM2026.04		62.77	79.71
ATR-Net2026.04		61.17	76.57
FRN2026.04		60.41	79.26
DAN2026.04		59.81	77.19
PaCL2026.04		59.76	77.5
GNN+2019.03		46.98	62.27
DeepEMD2026.04		46.73	65.74
DN4-DA2019.03		45.73	66.33
LRPABN2026.04		45.72	60.94
DN42019.03		45.41	63.51
DSN2026.04		44.52	59.42
Prototypical Nets+2019.03		37.59	48.19
Matching Nets FCE+2019.03		35.8	47.5
NBNN (Deep local features)2019.03		31.42	42.17
k-NN (Deep global features)2019.03		26.14	43.14