Image Classification on ImageNet-R 1.0 (val)
71.1Top-1 AccFAN-L-Hybrid
Evaluation Results
| Method | Links | |
|---|---|---|
| FAN-L-HybridParams (M)=76.8, Pre-trained=ImageNet-22K, Resolution=384x3842022.04 | 71.1 | |
| ConvNeXt-XLData/Size=22K/384^2, FLOPs (G)=179, Params (M)=350.22022.01 | 68.2 | |
| ConvNeXt-LData/Size=22K/384^2, FLOPs (G)=101, Params (M)=197.82022.01 | 66.7 | |
| ConvNeXt-BData/Size=22K/384^2, FLOPs (G)=45.1, Params (M)=88.62022.01 | 64.9 | |
| ConvNeXt-BParams (M)=88.6, Pre-trained=ImageNet-22K, Resolution=384x3842022.04 | 64.9 | |
| FAN-L-HybridParams (M)=76.8, Pre-trained=ImageNet-22K, Resolution=224x2242022.04 | 64.3 | |
| Swin-BParams (M)=87.8, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 64.2 | |
| MAEModel=ViT-L, Mixup and CutMix=w/ Mixup and CutMix2022.09 | 60.3 | |
| GPaCoModel=ViT-L, Mixup and CutMix=w/o Mixup and CutMix2022.09 | 60.3 | |
| MAE-VIT-LParams (M)=307, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 59.9 | |
| MAEModel=ViT-L, Mixup and CutMix=w/o Mixup and CutMix2022.09 | 55.3 | |
| FAN-L-HybridParams (M)=76.8, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 53.2 | |
| FAN-L-VITParams (M)=80.5, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 53.1 | |
| FAN-B-HybridParams (M)=50.0, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 52.9 | |
| RVT-B*Pre-training=ImageNet-22K, Fine-tuning=ImageNet-1K2021.05 | 52.63 | |
| DeiT-BPre-training=ImageNet-22K, Fine-tuning=ImageNet-1K2021.05 | 52.37 | |
| FAN-B-VITParams (M)=54.0, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 51.8 | |
| GPaCoModel=ViT-B, Mixup and CutMix=w/o Mixup and CutMix2022.09 | 51.7 | |
| ConvNeXt-BData/Size=1K/224^2, FLOPs (G)=15.4, Params (M)=88.62022.01 | 51.3 | |
| ConvNeXt-BParams (M)=88.6, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 51.3 | |
| FAN-S-HybridParams (M)=26.0, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 50.7 | |
| FAN-S-ViTParams (M)=28.0, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 50.4 | |
| MAEModel=ViT-B, Mixup and CutMix=w/ Mixup and CutMix2022.09 | 49.9 | |
| RVT-BPre-training=ImageNet-22K, Fine-tuning=ImageNet-1K2021.05 | 49.67 | |
| ConvNeXt-SParams (M)=50.2, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 49.5 | |
| RVT-B*Data/Size=1K/224^2, FLOPs (G)=17.7, Params (M)=91.82022.01 | 48.7 | |
| RVT-B*Params (M)=91.8, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 48.7 | |
| MAE-VIT-BParams (M)=86, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 48.3 | |
| RVT-S*Data/Size=1K/224^2, FLOPs (G)=4.7, Params (M)=23.32022.01 | 47.7 | |
| RVT-S*Params (M)=23.3, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 47.7 | |
| ConvNeXt-TData/Size=1K/224^2, FLOPs (G)=4.5, Params (M)=28.62022.01 | 47.2 | |
| ConvNeXt-TParams (M)=28.6, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 47.2 | |
| Swin-BData/Size=1K/224^2, FLOPs (G)=15.4, Params (M)=87.82022.01 | 46.6 | |
| Swin-SParams (M)=50, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 46.6 | |
| XCIT-S12Params (M)=26.3, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 45.5 | |
| XCiT-S24Params (M)=47.7, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 45.5 | |
| MAEModel=ViT-B, Mixup and CutMix=w/o Mixup and CutMix2022.09 | 44.9 | |
| Swin-TData/Size=1K/224^2, FLOPs (G)=4.5, Params (M)=28.32022.01 | 41.3 | |
| Swin-TParams (M)=28.3, Pre-trained=ImageNet-1K, Resolution=224x2242022.04 | 41.3 | |
| BYOL + Patch-basedalpha=0.052021.10 | 41.16 | |
| GPaCoModel=ResNet-50, Mixup and CutMix=w/o Mixup and CutMix2022.09 | 41.1 | |
| InfoMin2021.10 | 40.68 | |
| Supervised2021.10 | 39.76 | |
| BYOL2021.10 | 39.53 | |
| MoCo-v2 + Patch-basedalpha=2, training setting=IFM setting2021.10 | 38.45 | |
| MoCo-v2 + IFMepsilon=0.1, training setting=IFM setting2021.10 | 37.23 | |
| MoCo-v2 + IFMepsilon=0.2, training setting=IFM setting2021.10 | 37.14 | |
| MoCo-v2 + Patch-basedmemory bank size (k)=16384, alpha=32021.10 | 36.89 | |
| MoCo-v2 + IFMepsilon=0.05, training setting=IFM setting2021.10 | 36.79 | |
| MoCo-v2 + Patch-basedmemory bank size (k)=8192, alpha=22021.10 | 36.31 | |
| ResNet-50Data/Size=1K/224^2, FLOPs (G)=4.1, Params (M)=25.62022.01 | 36.1 | |
| MoCo-v2 + Patch-basedmemory bank size (k)=16384, alpha=22021.10 | 34.78 | |
| MoCo-v2 + Texture-basedmemory bank size (k)=16384, alpha=22021.10 | 33.36 | |
| MoCo-v2memory bank size (k)=81922021.10 | 33.19 | |
| MoCo-v2memory bank size (k)=163842021.10 | 32.92 | |
| CMC2021.10 | 32.68 | |
| MoCo-v2training setting=IFM setting, memory bank size (k)=163842021.10 | 30.38 | |
| InsDis2021.10 | 19.6 |