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Image Classification on CIFAR-100 (test)

94.55AccuracyVision Transformer (ViT-H/14)
86.146888.328490.5192.6916Jul 3, 2019Aug 8, 2020Sep 14, 2021Oct 21, 2022Nov 27, 2023Jan 2, 2025Feb 9, 2026

Evaluation results

MethodLinks
Vision Transformer (ViT-H/14)Pre-training Dataset=JFT-300M, Architecture=ViT-H/142020.1094.55——————————————————————————————————
Vision Transformer (ViT-L/16)Pre-training Dataset=JFT-300M, Architecture=ViT-L/162020.1093.9——————————————————————————————————
BiT-LArchitecture=ResNet152x42020.1093.51——————————————————————————————————
Vision Transformer (ViT-L/16)Pre-training Dataset=ImageNet-21k, Architecture=ViT-L/162020.1093.25——————————————————————————————————
Res-TuningParam. (M)=0.48 (0.55%), Mem.=6.85G2023.1093.25——————————————————————————————————
SAMPa-0.2Backbone=ViT-B/16, Pre-trained=Yes, Evaluation Protocol=Fine-tuning, Epochs=10, Optimizer=AdamW2024.1093.06——————————————————————————————————
EfficientNetV2-LParams=121M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0492.3——————————————————————————————————
EfficientNetV2-MParams=55M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0492.2——————————————————————————————————
AdaptFormerParam. (M)=1.26 (1.46%), Mem.=6.32G2023.1091.86——————————————————————————————————
SAMBackbone=ViT-B/16, Pre-trained=Yes, Evaluation Protocol=Fine-tuning, Epochs=10, Optimizer=AdamW2024.1091.79——————————————————————————————————
R50+ViT-B_16Backbone=R50+ViT-B_16, Pre-trained=ImageNet-21k, Evaluation Protocol=Fine-tuned2021.0691.71——————————————————————————————————
EfficientNet-B7Params=66M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0491.7——————————————————————————————————
CMT-Spre-training=true, batch size=10242022.0991.7——————————————————————————————————
MAM-AdapterParam. (M)=10.08 (11.72%), Mem.=9.57G2023.1091.7——————————————————————————————————
BiT-M R101x3Backbone=BiT-M R101x3, Pre-trained=ImageNet-21k, Evaluation Protocol=Fine-tuned2021.0691.55——————————————————————————————————
EfficientNetV2-SParams=24M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0491.5——————————————————————————————————
GPipeParams=556M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0491.3——————————————————————————————————
MoCo v3Backbone=ViT-H, Pre-training=ImageNet-1k Self-Supervised, Evaluation Protocol=End-to-end fine-tuning2021.0491.2——————————————————————————————————
MoCo v3Backbone=ViT-L, Pre-training=ImageNet-1k Self-Supervised, Evaluation Protocol=End-to-end fine-tuning2021.0491.1——————————————————————————————————
ASF-former-BParams (M)=56.72022.0491——————————————————————————————————
ViT-B_16Backbone=ViT-B_16, Pre-trained=ImageNet-21k, Evaluation Protocol=Fine-tuned2021.0690.95——————————————————————————————————
DeiT-BParams=86M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0490.8——————————————————————————————————
DeiT-B-384Params=86M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0490.8——————————————————————————————————
ViTAE-S+384Params (M)=23.62022.0490.8——————————————————————————————————
CeiT-S+384Params (M)=24.22022.0490.8——————————————————————————————————
DeiT-B+384Params (M)=86.62022.0490.8——————————————————————————————————
MoCo v3Backbone=ViT-B, Pre-training=ImageNet-1k Self-Supervised, Evaluation Protocol=End-to-end fine-tuning2021.0490.5——————————————————————————————————
MLP-Mixer-B_16Backbone=MLP-Mixer-B_16, Pre-trained=ImageNet-21k, Evaluation Protocol=Fine-tuned2021.0690.4——————————————————————————————————
ASF-former-SParams (M)=19.32022.0490.4——————————————————————————————————
Ens.Model=ViT-B/162025.1290.27——————————————————————————————————
TNT-S+384Params (M)=23.82022.0490.1——————————————————————————————————
ASAMBackbone=PyramidNet-272, rho=12021.0289.9——————————————————————————————————
Swin-T + matched inference + fuzzy relaxationpre-training=true, batch size=1282022.0989.6——————————————————————————————————
DPSModel=ViT-B/162025.1289.54——————————————————————————————————
Swin-T + smoothed focuspre-training=true, batch size=1282022.0989.53——————————————————————————————————
Swin-T + matched inferencepre-training=true, batch size=1282022.0989.39——————————————————————————————————
SAMBackbone=PyramidNet-272, rho=0.12021.0289.36——————————————————————————————————
PS-KDModel=ViT-B/162025.1289.36——————————————————————————————————
KDModel=ViT-B/162025.1289.35——————————————————————————————————
Res-Tuning-BypassParam. (M)=0.46 (0.53%), Mem.=4.72G2023.1089.33——————————————————————————————————
Swin-T + matched inference + Ldrlocpre-training=true, batch size=1282022.0989.29——————————————————————————————————
Swin-T + Ldrlocpre-training=true, batch size=1282022.0989.27——————————————————————————————————
Swin-T + relaxed self-attentionpre-training=true, batch size=1282022.0989.21——————————————————————————————————
Swin-T (resimulated baseline)pre-training=true, batch size=1282022.0989.16——————————————————————————————————
BaselineModel=ViT-B/162025.1289.16——————————————————————————————————
FullParam. (M)=85.9 (100%), Mem.=9.02G2023.1089.12——————————————————————————————————
TEModel=ViT-B/162025.1289.11——————————————————————————————————
ViT-B/16-SAMBackbone=ViT-B/16, SAM Pre-training=true, Resolution=224x2242021.0689.1——————————————————————————————————
SGDBackbone=PyramidNet-2722021.0288.91——————————————————————————————————
Swin-T + matched inferencepre-training=true, batch size=10242022.0988.73——————————————————————————————————
LSTParam. (M)=0.93 (1.08%), Mem.=5.26G2023.1088.72——————————————————————————————————
DLBModel=ViT-B/162025.1288.72——————————————————————————————————
Swin-T + relaxed self-attentionpre-training=true, batch size=10242022.0988.64——————————————————————————————————
Swin-T + Ldrlocpre-training=true, batch size=10242022.0988.63——————————————————————————————————
Swin-T + matched inference + fuzzy relaxationpre-training=true, batch size=10242022.0988.63——————————————————————————————————
Swin-T + matched inference + Ldrlocpre-training=true, batch size=10242022.0988.55——————————————————————————————————
Swin-T (resimulated baseline)pre-training=true, batch size=10242022.0988.53——————————————————————————————————
Swin-T + smoothed focuspre-training=true, batch size=10242022.0988.44——————————————————————————————————
Swin-T - stochastic depthpre-training=true, batch size=1282022.0988.42——————————————————————————————————
Swin-T + matched inference - stochastic depthpre-training=true, batch size=1282022.0988.42——————————————————————————————————
T2T-ViT-14pre-training=true, batch size=10242022.0988.4——————————————————————————————————
Swin-T (+ Ldrloc)pre-training=true, batch size=10242022.0988.4——————————————————————————————————
T2T-ViT-14Params (M)=21.52022.0488.4——————————————————————————————————
Swin-T (vanilla)pre-training=true, batch size=10242022.0988.22——————————————————————————————————
SHiRABackbone=ViT-Base, Evaluation Protocol=Fine-tuned2024.0688.15——————————————————————————————————
Global DEPre-train=Self-supervised (SSL), Backbone=ResNet-50, Ensemble Size=52023.0388.1——————————————————————————————————
EfficientNet-B0MAdds (M)=400, Params (M)=4, Search Method=manual, Year=20192026.0288.1——————————————————————————————————
MOEA-BUS-XLMAdds (M)=657, Params (M)=6.3, Search Cost (GPU Days)=1.2, Search Method=EA2026.0288.01——————————————————————————————————
LoRABackbone=ViT-Base, Evaluation Protocol=Fine-tuned2024.0687.97——————————————————————————————————
ResNet-152-SAMBackbone=ResNet-152, SAM Pre-training=true, Resolution=224x2242021.0687.8——————————————————————————————————
StarSSE (opt.)Pre-train=Self-supervised (SSL), Backbone=ResNet-50, Ensemble Size=52023.0387.63——————————————————————————————————
Swin-T - stochastic depthpre-training=true, batch size=10242022.0987.62——————————————————————————————————
ViT-S/16-SAMBackbone=ViT-S/16, SAM Pre-training=true, Resolution=224x2242021.0687.6——————————————————————————————————
ViT-B/16Backbone=ViT-B/16, SAM Pre-training=false, Resolution=224x2242021.0687.6——————————————————————————————————
MOEA-BUS-LMAdds (M)=458, Params (M)=6.24, Search Cost (GPU Days)=1.2, Search Method=EA2026.0287.53——————————————————————————————————
Swin-T + matched inference - stochastic depthpre-training=true, batch size=10242022.0987.49——————————————————————————————————
Local DEPre-train=Self-supervised (SSL), Backbone=ResNet-50, Ensemble Size=52023.0387.33——————————————————————————————————
FairNAS-AInput Size=224x224, x+ (M)=391, SE and Swish=true2019.0787.3——————————————————————————————————
FairNAS-AMAdds (M)=391, Search Cost (GPU Days)=12, Search Method=EA, Year=20212026.0287.3——————————————————————————————————
SPNASParams (M)=6.7, Search Cost (GPU Days)=1.6, Search Method=EA, Year=20252026.0287.26——————————————————————————————————
MOEA-BUS-MMAdds (M)=273, Params (M)=4.77, Search Cost (GPU Days)=1.2, Search Method=EA2026.0287.2——————————————————————————————————
Side-TuningParam. (M)=9.62 (11.18%), Mem.=3.48G2023.1087.16——————————————————————————————————
SSE (opt.)Pre-train=Self-supervised (SSL), Backbone=ResNet-50, Ensemble Size=52023.0387.11——————————————————————————————————
ViT-B/16Params=87M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0487.1——————————————————————————————————
ViT-L/32Params=306M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.0487.1——————————————————————————————————
MixNet-MInput Size=224x224, x+ (M)=3592019.0787.1——————————————————————————————————
ViT-S-16pre-training=true, batch size=10242022.0987.1——————————————————————————————————
ViT-B/16Params (M)=86.52022.0487.1——————————————————————————————————
ImNet supervisedBackbone=ViT-B, Pre-training=ImageNet-1k Supervised, Evaluation Protocol=End-to-end fine-tuning2021.0487.1——————————————————————————————————
BiT-M R50x1Backbone=BiT-M R50x1, Pre-trained=ImageNet-21k, Evaluation Protocol=Fine-tuned2021.0687.01——————————————————————————————————
FairNAS-BInput Size=224x224, x+ (M)=348, SE and Swish=true2019.0787——————————————————————————————————
FairNAS-BMAdds (M)=348, Search Cost (GPU Days)=12, Search Method=EA, Year=20212026.0287——————————————————————————————————
Global DEPre-train=Supervised (SV), Backbone=ResNet-50, Ensemble Size=52023.0386.82——————————————————————————————————
EfficientNet-B0Input Size=224x224, x+ (M)=3872019.0786.8——————————————————————————————————
MOEA-BUS-SMAdds (M)=198, Params (M)=4.19, Search Cost (GPU Days)=1.2, Search Method=EA2026.0286.71——————————————————————————————————
NASNet-A LargeInput Size=331x331, x+ (M)=120312019.0786.7——————————————————————————————————
FairNAS-CInput Size=224x224, x+ (M)=324, SE and Swish=true2019.0786.7——————————————————————————————————
NASNet-A LargeMAdds (M)=12031, Search Cost (GPU Days)=1800, Search Method=RL, Year=20182026.0286.7——————————————————————————————————
FairNAS-CMAdds (M)=324, Search Cost (GPU Days)=12, Search Method=EA, Year=20212026.0286.7——————————————————————————————————
SGD + GAMBackbone=PyramidNet110, Data Augmentation=RA2023.0386.47——————————————————————————————————