Image Classification on CIFAR100 (test) (Error Rate) benchmark leaderboard · SOTA2 Research

Image Classification on CIFAR100 (test) (Error Rate)

19.01Error RateFlatMatch

Evaluation Results

Method	Links
FlatMatch2023.10		19.01
FlatMatch (Fix label)2023.10		19.01
Fully-Supervised2023.10		19.3
FlatMatch-e2023.10		19.78
ReMixMatch2023.10		20.02
FreeMatch2023.10		21.68
MPL2023.10		21.74
FixMatch2023.10		21.88
FlexMatch2023.10		21.9
SoftMatch2023.10		22.03
UDA2023.10		22.2
Dash2023.10		22.49
FlatMatch2023.10		25.38
FlatMatch (Fix label)2023.10		25.38
FlatMatch-e2023.10		25.62
ReMixMatch2023.10		26.03
FreeMatch2023.10		26.47
FlexMatch2023.10		26.49
SoftMatch2023.10		26.66
FixMatch2023.10		27.15
MPL2023.10		27.71
Dash2023.10		27.73
MixMatch2023.10		27.78
UDA2023.10		28.03
Mean Teacher2023.10		31.75
VAT2023.10		32.14
Pseudo Label2023.10		36.55
Π-Model2023.10		36.65
FlatMatch (Fix label)2023.10		36.97
SoftMatch2023.10		37.1
FreeMatch2023.10		37.98
FlatMatch2023.10		38.76
FlatMatch-e2023.10		38.98
MixMatch2023.10		39.76
FlexMatch2023.10		39.94
ReMixMatch2023.10		42.75
FixMatch2023.10		44.82
Mean Teacher2023.10		45.17
MPL2023.10		46.26
Dash2023.10		46.39
UDA2023.10		46.42
VAT2023.10		46.84
Pseudo Label2023.10		57.74
Π-Model2023.10		58.8
MixMatch2023.10		67.59
Mean Teacher2023.10		81.11
VAT2023.10		85.2
Π-Model2023.10		86.96
Pseudo Label2023.10		87.45