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ResearchFormerly WizWand

Few-shot classification on Plantae

72.91AccuracySupervised
36.728446.121755.51564.9083Jan 23, 2020Jul 30, 2020Feb 4, 2021Aug 12, 2021Feb 17, 2022Aug 25, 2022Mar 2, 2023
Updated 8mo ago

Evaluation results

MethodLinks
SupervisedBackbone=ResNet-50, Evaluation protocol=5-way 5-shot2023.0372.91——
PsCoBackbone=ResNet-50, Base Method=BYOL, Evaluation protocol=5-way 5-shot2023.0371.14——
PsCoBackbone=ResNet-50, Base Method=MoCo v2, Evaluation protocol=5-way 5-shot2023.0369.17——
PsCoway=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0364.53——
PsCoBackbone=ResNet-18, Base Method=MoCo v2, Evaluation protocol=5-way 5-shot2023.0361.55——
MoCo v2Backbone=ResNet-50, Evaluation protocol=5-way 5-shot2023.0361.36——
BYOLBackbone=ResNet-50, Evaluation protocol=5-way 5-shot2023.0356.86——
MoCo v2Backbone=ResNet-18, Evaluation protocol=5-way 5-shot2023.0356.24——
MoCo v2way=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0355.45——
SimCLRway=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0354.92——
MAMLway=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0354.86——
ProtoNetsway=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0354.29——
SWAVway=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0354.03——
GNN (FT)Backbone=ResNet-10, Training Dataset=mini-ImageNet, FT (Feature-wise Transformation)=true2020.0153.85——
PsCoway=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0352.72——
GNNBackbone=ResNet-10, Training Dataset=mini-ImageNet, FT (Feature-wise Transformation)=false2020.0152.53——
MAMLway=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0347.33——
MatchingNetBackbone=ResNet-10, Training Dataset=mini-ImageNet, FT (Feature-wise Transformation)=false2020.0146.53——
MetaOptNet-SVM-trainvalBackbone=ResNet-12, Training Dataset=mini-ImageNet, FT (Feature-wise Transformation)=false2020.0146.48——
Meta-SVEBMway=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0346.22——
ProtoNetsway=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0345.89——
RelationNet (FT)Backbone=ResNet-10, Training Dataset=mini-ImageNet, FT (Feature-wise Transformation)=true2020.0145.08——
Meta-GMVAEway=5, shot=20, Backbone=Conv5, Pre-trained=miniImageNet2023.0345.02——
RelationNetBackbone=ResNet-10, Training Dataset=mini-ImageNet, FT (Feature-wise Transformation)=false2020.0144——
MoCo v2way=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0343.97——
SimCLRway=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0343.42——
SWAVway=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0342.68——
MatchingNet (FT)Backbone=ResNet-10, Training Dataset=mini-ImageNet, FT (Feature-wise Transformation)=true2020.0141.69——
Meta-GMVAEway=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0338.27——
Meta-SVEBMway=5, shot=5, Backbone=Conv5, Pre-trained=miniImageNet2023.0338.12——
GNNTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—33.648.51
GNN + ATATraining dataset=mini-ImageNet, Number of ways=5-way2021.04—34.4252.69
GNN + FTTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—32.5649.66
GNN + LRPTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—33.250.31
RelationNetTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—31.2342.71
RelationNet + ATATraining dataset=mini-ImageNet, Number of ways=5-way2021.04—33.7245.32
RelationNet + FTTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—32.5744.29
RelationNet + LRPTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—32.1143.7
TPNTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—37.450.96
TPN + ATATraining dataset=mini-ImageNet, Number of ways=5-way2021.04—39.8355.08
TPN + FTTraining dataset=mini-ImageNet, Number of ways=5-way2021.04—32.4643.2