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ResearchFormerly WizWand

Image Classification on CIFAR100 (test)

91.9Test AccuracyGLA
73.117677.993882.8787.7462Feb 20, 2020Sep 28, 2020May 8, 2021Dec 16, 2021Jul 25, 2022Mar 4, 2023Oct 12, 2023
Updated 8mo ago

Evaluation results

MethodLinks
GLAbackbone=ViT-B/162023.1091.9——
GLABackbone=CLIP ViT-B/162023.1091.9——
WiSE-FTbackbone=ViT-B/162023.1091.3——
WiSE-FTBackbone=CLIP ViT-B/162023.1091.3——
End-to-end fine-tuningbackbone=ViT-B/162023.1091——
E2EBackbone=CLIP ViT-B/16, Protocol=end-to-end fine-tuning2023.1091——
GLAbackbone=ViT-B/322023.1090.7——
GLABackbone=CLIP ViT-B/322023.1090.7——
WiSE-FTbackbone=ViT-B/322023.1090——
WiSE-FTBackbone=CLIP ViT-B/322023.1090——
End-to-end fine-tuningbackbone=ViT-B/322023.1089.4——
E2EBackbone=CLIP ViT-B/32, Protocol=end-to-end fine-tuning2023.1089.4——
Linear probebackbone=ViT-B/162023.1083.1——
LPBackbone=CLIP ViT-B/16, Protocol=linear probe2023.1083.1——
MaxUp + CutoutBackbone=WideResNet-28-10, Data Augmentation Strategy=MaxUp + Cutout, m (sample size)=102020.0282.48——
CutoutBackbone=WideResNet-28-10, Data Augmentation Strategy=Cutout2020.0281.59——
Linear probebackbone=ViT-B/322023.1080.5——
LPBackbone=CLIP ViT-B/32, Protocol=linear probe2023.1080.5——
RMSGDNetwork=ResNet101, Augmentation=Cutout2022.0380.36——
RMSGDNetwork=ResNet50, Augmentation=Cutout2022.0380.06——
SGDPNetwork=ResNet101, Augmentation=Cutout2022.0380.03——
RMSGDNetwork=ResNet34, Augmentation=Cutout2022.0379.7——
SGDPNetwork=ResNet34, Augmentation=Cutout2022.0379.67——
Teacher BaselineTeacher=resnet32x42020.0679.63——
Teacher BaselineTeacher=resnet32x42020.0679.63——
SGDPNetwork=ResNet50, Augmentation=Cutout2022.0379.52——
SAMNetwork=ResNet101, Augmentation=Cutout2022.0379.41——
SGDNetwork=ResNet101, Augmentation=Cutout2022.0379.35——
Teacher BaselineTeacher=ResNet502020.0679.1——
Teacher BaselineTeacher=ResNet502020.0679.1——
SGDPNetwork=ResNet18, Augmentation=Cutout2022.0378.82——
SGDNetwork=ResNet34, Augmentation=Cutout2022.0378.63——
SSKDTeacher=resnet32x4, Student=ShuffleV22020.0678.61——
SAMNetwork=ResNet34, Augmentation=Cutout2022.0378.57——
RMSGDNetwork=ResNet18, Augmentation=Cutout2022.0378.53——
SSKDTeacher=resnet32x4, Student=ShuffleV12020.0678.44——
SGDNetwork=ResNet50, Augmentation=Cutout2022.0378.36——
SGDNetwork=ResNet18, Augmentation=Cutout2022.0378.16——
RMSGDNetwork=ResNeXt, Augmentation=Cutout2022.0378.06——
PDC-NLNumber of parameters=12.00 x 10^6, variant=42021.0477.9——
SGDNetwork=SENet18, Augmentation=Cutout2022.0377.8——
RMSGDNetwork=SENet18, Augmentation=Cutout2022.0377.77——
SAMNetwork=ResNet50, Augmentation=Cutout2022.0377.73——
SGDPNetwork=SENet18, Augmentation=Cutout2022.0377.7——
SAMNetwork=SENet18, Augmentation=Cutout2022.0377.64——
SAMNetwork=ResNet18, Augmentation=Cutout2022.0377.58——
SSKDTeacher=wrn40-2, Student=ShuffleV12020.0677.4——
PDC-NLNumber of parameters=11.87 x 10^6, variant=32021.0477.3——
SGDPNetwork=ResNeXt, Augmentation=Cutout2022.0377.14——
DNLNumber of parameters=11.57 x 10^62021.0477.1——
NLNumber of parameters=11.57 x 10^62021.0476.9——
ABTeacher=wrn40-2, Student=ShuffleV12020.0676.58——
Teacher BaselineTeacher=wrn40-22020.0676.46——
RMSGDNetwork=MobileNetV2, Augmentation=Cutout2022.0376.36——
SAMNetwork=ResNeXt, Augmentation=Cutout2022.0376.34——
ABTeacher=resnet32x4, Student=ShuffleV12020.0676.24——
CRDTeacher=wrn40-2, Student=ShuffleV12020.0675.96——
SGDNetwork=ResNeXt, Augmentation=Cutout2022.0375.91——
VIDTeacher=resnet32x4, Student=ShuffleV22020.0675.78——
SSKDTeacher=ResNet50, Student=vgg82020.0675.76——
RKDTeacher=resnet32x4, Student=ShuffleV22020.0675.74——
CRDTeacher=resnet32x4, Student=ShuffleV22020.0675.72——
ABTeacher=resnet32x4, Student=ShuffleV22020.0675.66——
MaxUp + CutoutBackbone=PreAct-ResNet-110, Data Augmentation Strategy=MaxUp + Cutout2020.0275.63——
ATTeacher=wrn40-2, Student=ShuffleV12020.0675.61——
ResNet18Number of parameters=11.2 x 10^62021.0475.6——
SPTeacher=wrn40-2, Student=ShuffleV12020.0675.56——
FitNetTeacher=wrn40-2, Student=ShuffleV12020.0675.55——
PKTTeacher=wrn40-2, Student=ShuffleV12020.0675.51——
CRDTeacher=resnet32x4, Student=ShuffleV12020.0675.46——
RKDTeacher=wrn40-2, Student=ShuffleV12020.0675.45——
SAMNetwork=MobileNetV2, Augmentation=Cutout2022.0375.43——
Teacher BaselineTeacher=vgg132020.0675.38——
VIDTeacher=wrn40-2, Student=ShuffleV12020.0675.36——
ATTeacher=resnet32x4, Student=ShuffleV22020.0675.3——
MaxUp + CutoutBackbone=ResNet-110, Data Augmentation Strategy=MaxUp + Cutout, m (sample size)=42020.0275.26——
PKTTeacher=resnet32x4, Student=ShuffleV22020.0675.18——
FTTeacher=wrn40-2, Student=ShuffleV12020.0675.18——
SPTeacher=resnet32x4, Student=ShuffleV22020.0675.15——
FitNetTeacher=resnet32x4, Student=ShuffleV22020.0675.11——
FTTeacher=resnet32x4, Student=ShuffleV22020.0674.95——
KDTeacher=wrn40-2, Student=ShuffleV12020.0674.83——
FitNetTeacher=resnet32x4, Student=ShuffleV12020.0674.82——
ATTeacher=resnet32x4, Student=ShuffleV12020.0674.76——
SAMNetwork=ShuffleNetV2, Augmentation=Cutout2022.0374.7——
KDTeacher=resnet32x4, Student=ShuffleV22020.0674.45——
SGDPNetwork=ShuffleNetV2, Augmentation=Cutout2022.0374.44——
CRDTeacher=ResNet50, Student=vgg82020.0674.42——
RMSGDNetwork=ShuffleNetV2, Augmentation=Cutout2022.0374.38——
CutoutBackbone=PreAct-ResNet-110, Data Augmentation Strategy=Cutout2020.0274.37——
FTTeacher=resnet32x4, Student=ShuffleV12020.0674.31——
VIDTeacher=resnet32x4, Student=ShuffleV12020.0674.28——
ABTeacher=ResNet50, Student=vgg82020.0674.2——
RKDTeacher=resnet32x4, Student=ShuffleV12020.0674.2——
SGDNetwork=ShuffleNetV2, Augmentation=Cutout2022.0374.13——
KDTeacher=resnet32x4, Student=ShuffleV12020.0674.07——
PKTTeacher=resnet32x4, Student=ShuffleV12020.0674.06——
SGDNetwork=MobileNetV2, Augmentation=Cutout2022.0373.94——
SPTeacher=ResNet50, Student=vgg82020.0673.86——
FitNetTeacher=ResNet50, Student=vgg82020.0673.84——