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ResearchFormerly WizWand

Semi-supervised Image Classification on CUB200 (10% train)

81.23AccuracyDGCG
9.251627.938346.62565.3117May 23, 2026
Updated 5mo ago

Evaluation results

MethodLinks
DGCGFeatures=ViT-B162026.0581.23
MGCNFeatures=ViT-B162026.0579.27
WSEFFeatures=ViT-B162026.0578.64
GRaNDeFeatures=ViT-B162026.0578.58
SVMFeatures=ViT-B162026.0575.61
OPFFeatures=ViT-B162026.0573.27
LS+ SVMFeatures=ViT-B162026.0566.81
LS+ OPFFeatures=ViT-B162026.0566.68
LS+ kNNFeatures=ViT-B162026.0566.15
LS+ ML-Perc.Features=ViT-B162026.0562.81
GRaNDeFeatures=ResNet2026.0554.58
DGCGFeatures=ResNet2026.0554.43
MGCNFeatures=ResNet2026.0552.85
GNN-LDSFeatures=ViT-B162026.0552.42
WSEFFeatures=ResNet2026.0552.17
SVMFeatures=ResNet2026.0548.84
GRaNDeFeatures=SENet2026.0543.78
DGCGFeatures=SENet2026.0541
MGCNFeatures=SENet2026.0540.31
LS+ ML-Perc.Features=ResNet2026.0539.68
LS+ OPFFeatures=ResNet2026.0539.28
LS+ SVMFeatures=ResNet2026.0538.7
OPFFeatures=ResNet2026.0538.59
CoMatch2026.0538.29
GNN-LDSFeatures=ResNet2026.0537.78
LS+ kNNFeatures=ResNet2026.0536.99
WSEFFeatures=SENet2026.0536.49
SVMFeatures=SENet2026.0535.32
ML-Perc.Features=ResNet2026.0532.24
ML-Perc.Features=SENet2026.0532.15
OPFFeatures=SENet2026.0530.94
PL+ SGDFeatures=ViT-B162026.0530.19
LS+ ML-Perc.Features=SENet2026.0525.72
LS+ OPFFeatures=SENet2026.0525.38
LS+ SVMFeatures=SENet2026.0524.82
PL+ SGDFeatures=ResNet2026.0521.67
PL+ SGDFeatures=SENet2026.0520.96
LS+ kNNFeatures=SENet2026.0520
ML-Perc.Features=ViT-B162026.0512.02