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ResearchFormerly WizWand

OOD Detection on NINCO

46.22FPR95RMDS
44.236457.625771.01584.4043Apr 29, 2026May 6, 2026May 14, 2026May 22, 2026May 30, 2026Jun 7, 2026Jun 15, 2026
Updated 4mo ago

Evaluation results

MethodLinks
RMDSBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0446.2287.31
EPDBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0448.0685.74
MDSBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0448.7686.52
Maha++Backbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0650.2988.42
rMaha++Backbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0650.2988.42
rMahaBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0650.9488.28
X-MahaBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0651.7588.71
MahaBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0651.8987.95
FDBDModel=DINOv22026.0554.4181.52
KNNBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0454.7382.25
SHEBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0456.0184.18
rMaha++Backbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0656.2186.32
ViMBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0457.4584.64
OCOModel=DINOv22026.0557.7481.27
Maha++Backbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0657.7985.87
OODDModel=DINOv22026.0558.6881.3
GENBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0459.3182.51
CoRPModel=DINOv22026.0559.3680.31
MM++Backbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0660.0785.55
OCOModel=ViT2026.0560.7781.84
SHEModel=DINOv22026.0562.2379.76
MSPBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0662.2880.99
EnergyBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0662.3575.62
ReActBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0662.3576.17
NECOModel=DINOv22026.0563.6477.19
MaxLogitModel=DINOv22026.0563.7577.08
SCALEModel=DINOv22026.0563.9875.83
EnergyModel=DINOv22026.0564.6575.78
MaxLogitModel=ViT2026.0566.1979.92
SCALEModel=ViT2026.0566.5479.75
EnergyModel=ViT2026.0567.3979.17
OODDModel=ViT2026.0567.5277.12
FDBDModel=ViT2026.0568.979.15
CoRPModel=ViT2026.0570.4272.63
rMahaBackbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0670.583.59
MSPBackbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0670.5280.3
ReActBackbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0672.2278.62
EnergyBackbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0672.4277.1
ODINBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0672.871.31
MM++Backbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0672.8782.06
NNguideModel=ViT2026.0575.0570.65
NNguideModel=DINOv22026.0575.4367.77
MSPBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0477.3578.11
ReActBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0478.575.43
MahaBackbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0679.7680.46
KNNBackbone=EVA02-S14, ID Dataset=ImageNet-LT2026.0680.3972.75
DICEBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0481.0971.67
TempScaleBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0481.977.8
SHEModel=ViT2026.0582.2371.16
NECOModel=ViT2026.0583.0479.28
ODINBackbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0685.4167.68
OpenMaxBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0488.3678.68
MLSBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0492.9872.4
EBOBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0494.1666.02
KNNBackbone=Swin-T, In-Distribution (ID) Dataset=ImageNet-LT2026.0695.343.16
ASHBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0495.452.52
GradNormBackbone=ViT-B/16, ID Accuracy=81.14%, ID Dataset=ImageNet-1K2026.0495.8164.4