Image Classification on Oxford Flowers-102 (test)
99.847Top-1 AccuracyEfficient Adaptive Ensembling
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| Efficient Adaptive Ensemblingensemble size=2 weak models2022.06 | 99.847 | 0.127 | — | |
| ViT-L/16 + BackgroundArchitecture=ViT-L/16, Epochs=2, Spinal FC=false, Background Class=true2023.05 | 99.75 | — | — | |
| Vision Transformer (ViT-L/16)Pre-training Dataset=JFT-300M, Architecture=ViT-L/162020.10 | 99.74 | — | — | |
| SOTA2022.06 | 99.72 | — | — | |
| CvT-W24Param (M)=277, Pre-trained=ImageNet-22k2021.03 | 99.72 | — | — | |
| Vision Transformer (ViT-H/14)Pre-training Dataset=JFT-300M, Architecture=ViT-H/142020.10 | 99.68 | — | — | |
| BiT-LArchitecture=ResNet152x42020.10 | 99.63 | — | — | |
| CvT-21Param (M)=32, Pre-trained=ImageNet-22k2021.03 | 99.62 | — | — | |
| ViT-L/16Param (M)=307, Pre-trained=ImageNet-22k2021.03 | 99.61 | — | — | |
| Vision Transformer (ViT-L/16)Pre-training Dataset=ImageNet-21k, Architecture=ViT-L/162020.10 | 99.61 | — | — | |
| ViT-L/16 + (Spinal FC & Background)Architecture=ViT-L/16, Epochs=2, Spinal FC=true, Background Class=true2023.05 | 99.6 | — | — | |
| ViT-H/16Param (M)=632, Pre-trained=ImageNet-22k2021.03 | 99.51 | — | — | |
| ViT-L/16Architecture=ViT-L/16, Epochs=2, Spinal FC=false, Background Class=false2023.05 | 99.51 | — | — | |
| CvT-13Param (M)=20, Pre-trained=ImageNet-22k2021.03 | 99.5 | — | — | |
| ViT-L/16 + Spinal FCArchitecture=ViT-L/16, Epochs=2, Spinal FC=true, Background Class=false2023.05 | 99.41 | — | — | |
| ViT-B/16Param (M)=86, Pre-trained=ImageNet-22k2021.03 | 99.38 | — | — | |
| BiT-MParam (M)=928, Pre-trained=ImageNet-22k2021.03 | 99.3 | — | — | |
| Grafit RegNetY-8GFParams (M)=39.2, Resolution=384x384, Pre-training=ImageNet2021.02 | 99.1 | — | — | |
| Graph-PruneEpochs=100, Backbone=EfficientNet-B0, Pruning strategy=Eigenvector Centrality, Layer pruned=Final Dense layer2025.12 | 99.07 | — | — | |
| TNT-BParams (M)=65.6, Resolution=384x384, Pre-training=ImageNet2021.02 | 99 | — | — | |
| iBOTBackbone=ViT-B/16, Evaluation Protocol=Fine-tuning2021.11 | 98.9 | — | — | |
| DeiT-BGPU Throughput (images/sec)=114, Resolution=384x384, Fine-tuned=true2026.03 | 98.9 | — | — | |
| LowFormer-B3GPU Throughput (images/sec)=424, Resolution=384x384, Fine-tuned=true2026.03 | 98.9 | — | — | |
| GPipeParams=556M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.04 | 98.8 | — | — | |
| EfficientNet-B7Params=66M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.04 | 98.8 | — | — | |
| EfficientNetV2-LParams=121M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.04 | 98.8 | — | — | |
| TNT-SParams (M)=23.8, Resolution=384x384, Pre-training=ImageNet2021.02 | 98.8 | — | — | |
| DINOBackbone=ViT-B/16, Evaluation Protocol=Fine-tuning2021.11 | 98.8 | — | — | |
| DINOprotocol=Fine Tuning, arch.=ViT-B/162024.08 | 98.8 | — | — | |
| MoCo v3Backbone=ViT-H, Pre-training=ImageNet-1k Self-Supervised, Evaluation Protocol=End-to-end fine-tuning2021.04 | 98.8 | — | — | |
| TNT-SGPU Throughput (images/sec)=141, Resolution=384x384, Fine-tuned=true2026.03 | 98.8 | — | — | |
| iBOTBackbone=ViT-S/16, Evaluation Protocol=Fine-tuning2021.11 | 98.6 | — | — | |
| MoCo v3Backbone=ViT-L, Pre-training=ImageNet-1k Self-Supervised, Evaluation Protocol=End-to-end fine-tuning2021.04 | 98.6 | — | — | |
| CeiT-SGPU Throughput (images/sec)=260, Resolution=384x384, Fine-tuned=true2026.03 | 98.6 | — | — | |
| DeiT-B-384Params=86M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.04 | 98.5 | — | — | |
| EfficientNetV2-MParams=55M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.04 | 98.5 | — | — | |
| EfficientNet-B5Params (M)=30, Resolution=384x384, Pre-training=ImageNet2021.02 | 98.5 | — | — | |
| EfficientNet-B5Params (M)=30, Fine-tuning=true2021.06 | 98.5 | — | — | |
| DINOBackbone=ViT-S/16, Evaluation Protocol=Fine-tuning2021.11 | 98.5 | — | — | |
| EfficientNetV2-MGPU Throughput (images/sec)=277, Resolution=384x384, Fine-tuned=true2026.03 | 98.5 | — | — | |
| DeiT-BParams=86M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.04 | 98.4 | — | — | |
| DeiT-BParams (M)=86.4, Resolution=384x384, Pre-training=ImageNet2021.02 | 98.4 | — | — | |
| DeiT-BParams (M)=86.6, Fine-tuning=true2021.06 | 98.4 | — | — | |
| Rand.Backbone=ViT-B/16, Evaluation Protocol=Fine-tuning2021.11 | 98.4 | — | — | |
| Grafit ResNet-50Params (M)=25.6, Resolution=384x384, Pre-training=ImageNet2021.02 | 98.2 | — | — | |
| Grafit ResNet-50Params (M)=25.6, Fine-tuning=true2021.06 | 98.2 | — | — | |
| Rand.Backbone=ViT-S/16, Evaluation Protocol=Fine-tuning2021.11 | 98.2 | — | — | |
| DnCBackbone=ResNet-50, Pre-training dataset=JFT, Pre-training epochs=4500 ImageNet-equivalent, Evaluation protocol=Linear transfer2022.01 | 98.2 | — | — | |
| DIFFUSEMIXBackbone=ResNet-50, Pre-trained=ImageNet, Evaluation protocol=Fine-tuning2024.04 | 98.02 | — | — | |
| BEITBackbone=ViT-B/16, Evaluation Protocol=Fine-tuning2021.11 | 98 | — | — | |
| EfficientNetV2-SParams=24M, Pre-trained=ImageNet ILSVRC2012, Evaluation Protocol=finetuned2021.04 | 97.9 | — | — | |
| BAMprotocol=Fine Tuning, arch.=ViT-B/162024.08 | 97.9 | — | — | |
| ReXNet (x1.0)FLOPs=0.4B, Params=4.8M, Fine-tuning=true2020.07 | 97.8 | — | — | |
| ViTAE-SParams (M)=23.6, Fine-tuning=true2021.06 | 97.8 | — | — | |
| ImageNet - Adaptive TransferPre-training Method=ImageNet - Adaptive Transfer, Backbone=Inception v32018.11 | 97.7 | — | — | |
| EMD SubsetPre-training Method=ImageNet & iNaturalist - EMD Subset, Backbone=Inception v32018.11 | 97.7 | — | — | |
| ResNet50FLOPs=4.1B, Params=25.6M, Fine-tuning=true2020.07 | 97.7 | — | — | |
| MoCo-v3protocol=Fine Tuning, arch.=ViT-B/162024.08 | 97.7 | — | — | |
| MoCo v3Backbone=ViT-B, Pre-training=ImageNet-1k Self-Supervised, Evaluation Protocol=End-to-end fine-tuning2021.04 | 97.7 | — | — | |
| ViTAE-TParams (M)=4.8, Fine-tuning=true2021.06 | 97.5 | — | — | |
| EfficientNet-B0FLOPs=0.4B, Params=5.3M, Fine-tuning=true2020.07 | 97.3 | — | — | |
| AdaAugBackbone=ResNet-50, Pre-trained=ImageNet, Evaluation protocol=Fine-tuning2024.04 | 97.19 | — | — | |
| Entire ImageNet DatasetPre-training Method=Entire ImageNet Dataset, Backbone=Inception v32018.11 | 97.1 | — | — | |
| Selective Joint FTPre-training Method=ImageNet - Selective Joint FT, Backbone=Inception v32018.11 | 97 | — | — | |
| BEITBackbone=ViT-S/16, Evaluation Protocol=Fine-tuning2021.11 | 96.4 | — | — | |
| BAMprotocol=Linear Eval., arch.=ResNet-502024.08 | 96.3 | — | — | |
| BYOLprotocol=Linear Eval., arch.=ResNet-502024.08 | 96.1 | — | — | |
| Fast AABackbone=ResNet-50, Pre-trained=ImageNet, Evaluation protocol=Fine-tuning2024.04 | 96.08 | — | — | |
| NETTAILORBackbone=ResNet-50, Input Resolution=224x224, Number of Parameters=8.5M, FLOPs=2.37G2019.06 | 95.79 | — | — | |
| ReLICv2Backbone=ResNet-50, Pre-training dataset=JFT, Pre-training epochs=5000 ImageNet-equivalent, Evaluation protocol=Linear transfer2022.01 | 95.7 | — | — | |
| RABackbone=ResNet-50, Pre-trained=ImageNet, Evaluation protocol=Fine-tuning2024.04 | 95.23 | — | — | |
| NNCLRprotocol=Linear Eval., arch.=ResNet-502024.08 | 95.1 | — | — | |
| VanillaBackbone=ResNet-50, Pre-trained=ImageNet, Evaluation protocol=Fine-tuning2024.04 | 94.98 | — | — | |
| PiggybackBackbone=ResNet-50, Input Resolution=224x224, Number of Parameters=24.3M, FLOPs=4.11G2019.06 | 94.77 | — | — | |
| ReLICv2Backbone=ResNet-50, Pre-training dataset=JFT, Pre-training epochs=1000 ImageNet-equivalent, Evaluation protocol=Linear transfer2022.01 | 94.5 | — | — | |
| BYOLBackbone=ResNet-50, Pre-training dataset=JFT, Pre-training epochs=5000 ImageNet-equivalent, Evaluation protocol=Linear transfer2022.01 | 94.3 | — | — | |
| AABackbone=ResNet-50, Pre-trained=ImageNet, Evaluation protocol=Fine-tuning2024.04 | 93.88 | — | — | |
| REGSLBackbone=ResNet-101, Pre-trained=ImageNet (ILSVRC-2012), Evaluation Protocol=Fine-tuning2021.11 | 93.82 | — | — | |
| LSBackbone=ResNet-101, Pre-trained=ImageNet (ILSVRC-2012), Evaluation Protocol=Fine-tuning2021.11 | 93.72 | — | — | |
| l2-PGMBackbone=ResNet-101, Pre-trained=ImageNet (ILSVRC-2012), Evaluation Protocol=Fine-tuning2021.11 | 93.23 | — | — | |
| l2-SPBackbone=ResNet-101, Pre-trained=ImageNet (ILSVRC-2012), Evaluation Protocol=Fine-tuning2021.11 | 93.06 | — | — | |
| PackNet (Forward)Backbone=ResNet-50, Input Resolution=224x224, Order=CUB, Cars, Flowers, WikiArt, Sketch, Number of Parameters=23.9M, FLOPs=4.11G2019.06 | 93.04 | — | — | |
| Fine-tuningBackbone=ResNet-101, Pre-trained=ImageNet (ILSVRC-2012), Evaluation Protocol=Fine-tuning2021.11 | 92.92 | — | — | |
| l2-NormBackbone=ResNet-101, Pre-trained=ImageNet (ILSVRC-2012), Evaluation Protocol=Fine-tuning2021.11 | 92.76 | — | — | |
| ViT-baseParams.=86M, Complexity=O(N^2), Evaluation Protocol=Linear Probing2025.07 | 92.75 | — | — | |
| Structured PruningEpochs=100, Backbone=EfficientNet-B0, Pruning strategy=Structured Pruning, Layer pruned=Final Dense layer2025.12 | 92.37 | — | — | |
| ResNet50Epochs=100, Backbone=ResNet-50, Pruning strategy=None2025.12 | 91.96 | — | — | |
| ViT-B/16-SAMBackbone=ViT-B/16, SAM Pre-training=true2021.06 | 91.8 | — | — | |
| ViT-S/16-SAMBackbone=ViT-S/16, SAM Pre-training=true2021.06 | 91.5 | — | — | |
| SimCLRprotocol=Linear Eval., arch.=ResNet-502024.08 | 91.2 | — | — | |
| ResNet-152-SAMBackbone=ResNet-152, SAM Pre-training=true2021.06 | 91.1 | — | — | |
| EfficientNetEpochs=100, Backbone=EfficientNet-B0, Pruning strategy=None2025.12 | 91.04 | — | — | |
| EViTKeep rate r=0.7, Backbone=DeiT-S2026.04 | 90.81 | — | — | |
| Ours (Rényi, α = 5.0)Keep rate r=0.9, Backbone=DeiT-S2026.04 | 90.71 | — | — | |
| Ours (Rényi, α = 2.0)Keep rate r=0.7, Backbone=DeiT-S2026.04 | 90.63 | — | — | |
| EViTKeep rate r=0.9, Backbone=DeiT-S2026.04 | 90.58 | — | — | |
| PackNet (Reversed)Backbone=ResNet-50, Input Resolution=224x224, Order=Sketch, WikiArt, Flowers, Cars, CUB, Number of Parameters=23.9M, FLOPs=4.11G2019.06 | 90.55 | — | — | |
| Ours (Rényi, α = 5.0)Keep rate r=0.7, Backbone=DeiT-S2026.04 | 90.45 | — | — | |
| Ours (Shannon)Keep rate r=0.9, Backbone=DeiT-S2026.04 | 90.23 | — | — | |
| Ours (Rényi, α = 5.0)Keep rate r=0.8, Backbone=DeiT-S2026.04 | 90.14 | — | — |