Image Classification on CIFAR-100-LT Imbalance Ratio 100 (test)
89.1AccuracyLPT
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| LPTBackbone=ViT-B/16, Learnable Params.=1.01M, Epochs=40+40, Training Protocol=Fine-tuning pre-trained model from ImageNet-21K2023.09 | 89.1 | — | |
| LIFTBackbone=ViT-B/16, Learnable Params.=0.10M, Epochs=10, Training Protocol=Fine-tuning pre-trained model from ImageNet-21K2023.09 | 89.1 | — | |
| LIFT w/ TTEBackbone=ViT-B/16, Learnable Params.=0.10M, Epochs=10, Training Protocol=Fine-tuning pre-trained model2023.09 | 81.7 | — | |
| LIFTBackbone=ViT-B/16, Learnable Params.=0.10M, Epochs=10, Training Protocol=Fine-tuning pre-trained model2023.09 | 80.2 | — | |
| BALLADBackbone=ViT-B/16, Learnable Params.=149.62M, Epochs=50+10, Training Protocol=Fine-tuning pre-trained model2023.09 | 77.8 | — | |
| LiVTBackbone=ViT-B/16, Learnable Params.=85.80M, Epochs=100, Training Protocol=Fine-tuning pre-trained model2023.09 | 58.2 | — | |
| Meta-SuperDisco2023.03 | 53.8 | — | |
| Alshammari et al.Venue=CVPR 222023.03 | 53.3 | — | |
| Cui et al.Venue=ICCV 212023.03 | 52 | — | |
| PaCoBackbone=ResNet-32, Learnable Params.=0.46M, Epochs=400, Training Protocol=Training from scratch2023.09 | 52 | — | |
| Zhu et al.Venue=CVPR 222023.03 | 51.9 | — | |
| BCLBackbone=ResNet-32, Learnable Params.=0.46M, Epochs=200, Training Protocol=Training from scratch2023.09 | 51.9 | — | |
| BSBackbone=ResNet-32, Learnable Params.=0.46M, Epochs=400, Training Protocol=Training from scratch2023.09 | 50.8 | — | |
| Wang et al.Venue=ICLR 212023.03 | 48 | — | |
| Samuel et al.Venue=ICCV 212023.03 | 47.3 | — | |
| MiSLASBackbone=ResNet-32, Learnable Params.=0.46M, Epochs=200+10, Training Protocol=Training from scratch2023.09 | 47 | — | |
| Zhong et al.Venue=CVPR 212023.03 | 46.8 | — | |
| CBD + TailCalibXType=Ours2021.11 | 46.59 | — | |
| Li et al.Venue=CVPR 212023.03 | 46 | — | |
| ABSGD (CB-CE)Backbone=ResNet32, Loss Function=CB-CE2020.12 | 45.89 | — | |
| ABSGD (CB-LDAM)Backbone=ResNet32, Loss Function=CB-LDAM2020.12 | 45.65 | — | |
| ABSGD (CB-CE)Backbone=ResNet32, Loss Function=CB-CE2020.12 | 45.54 | — | |
| ABSGD (CB-Focal)Backbone=ResNet32, Loss Function=CB-Focal2020.12 | 45.41 | — | |
| DiVEBackbone=ResNet-32, Learnable Params.=0.46M, Epochs=200, Training Protocol=Training from scratch2023.09 | 45.4 | — | |
| SGD (CB-LDAM)Backbone=ResNet32, Loss Function=CB-LDAM2020.12 | 45.36 | — | |
| CBDType=Distillation, re-implementation=true2021.11 | 44.83 | — | |
| ABSGD (CB-LDAM)Backbone=ResNet32, Loss Function=CB-LDAM2020.12 | 44.71 | — | |
| META (CB-Focal)Backbone=ResNet32, Loss Function=CB-Focal2020.12 | 44.7 | — | |
| CosineCE + TailCalibXType=Ours2021.11 | 44.44 | — | |
| ABSGD (CB-Focal)Backbone=ResNet32, Loss Function=CB-Focal2020.12 | 44.11 | — | |
| GBMType=Loss or Re-weighting2021.11 | 44.1 | — | |
| META (CB-LDAM)Backbone=ResNet32, Loss Function=CB-LDAM2020.12 | 44.08 | — | |
| Logit adjustmentType=Loss or Re-weighting2021.11 | 43.89 | — | |
| META (CB-CE)Backbone=ResNet32, Loss Function=CB-CE2020.12 | 43.35 | — | |
| CosineCE + TailCalibType=Ours2021.11 | 43.03 | — | |
| M2MType=Generation2021.11 | 42.9 | — | |
| MODALSType=Generation, re-implementation=true2021.11 | 42.813 | — | |
| CRTType=Decouple, re-implementation=true2021.11 | 42.63 | — | |
| BBNBackbone=ResNet-32, Learnable Params.=0.46M, Epochs=200, Training Protocol=Training from scratch2023.09 | 42.6 | — | |
| BBNType=Decouple2021.11 | 42.56 | — | |
| LFMEType=Distillation2021.11 | 42.3 | — | |
| SGD (CB-LDAM)Backbone=ResNet32, Loss Function=CB-LDAM2020.12 | 42.04 | — | |
| LDAM-DRWType=Loss or Re-weighting2021.11 | 42.04 | — | |
| Park et al.Venue=ICCV 212023.03 | 42 | — | |
| LDAMBackbone=ResNet-32, Learnable Params.=0.46M, Epochs=200, Training Protocol=Training from scratch2023.09 | 42 | — | |
| Meta Weight NetType=Loss or Re-weighting2021.11 | 41.61 | — | |
| CosineCEType=Baseline, re-implementation=true2021.11 | 41.44 | — | |
| CEType=Baseline, re-implementation=true2021.11 | 39.89 | — | |
| SGD (LDAM)Backbone=ResNet32, Loss Function=LDAM2020.12 | 39.6 | — | |
| Class-Balanced FocalType=Loss or Re-weighting2021.11 | 39.6 | — | |
| SGD (LDAM)Backbone=ResNet32, Loss Function=LDAM2020.12 | 39.58 | — | |
| mixupType=Generation2021.11 | 39.54 | — | |
| Domain AdaptationType=Loss or Re-weighting2021.11 | 39.31 | — | |
| L2RWType=Loss or Re-weighting2021.11 | 38.9 | — | |
| ResamplingBackbone=ResNet32, Loss Function=CE2020.12 | 38.87 | — | |
| ResamplingBackbone=ResNet32, Loss Function=CE2020.12 | 38.84 | — | |
| SGD (CB-CE)Backbone=ResNet32, Loss Function=CB-CE2020.12 | 38.7 | — | |
| Focal LossType=Loss or Re-weighting2021.11 | 38.41 | — | |
| Manifold mixupType=Generation2021.11 | 38.25 | — | |
| SGD (CB-Focal)Backbone=ResNet32, Loss Function=CB-Focal2020.12 | 36.02 | — | |
| SGD (CB-CE)Backbone=ResNet32, Loss Function=CB-CE2020.12 | 21.31 | — | |
| SGD (CB-Focal)Backbone=ResNet32, Loss Function=CB-Focal2020.12 | 19.76 | — | |
| CB-CEBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 38.6 | |
| CB-FocalBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 39.6 | |
| CEBackbone=ResNet-32, Reproduced=true2021.04 | — | 38.32 | |
| CEBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 38.3 | |
| CE-DRSBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 40.4 | |
| CE-DRWBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 40.5 | |
| cRTBackbone=ResNet-32, Reproduced=true2021.04 | — | 41.24 | |
| DRO-LTBackbone=ResNet-32, Radius Config=ε = 0 (ERM)2021.04 | — | 43.92 | |
| DRO-LTBackbone=ResNet-32, Radius Config=Shared ε2021.04 | — | 45.66 | |
| DRO-LTBackbone=ResNet-32, Radius Config=ε/√n2021.04 | — | 46.92 | |
| DRO-LTBackbone=ResNet-32, Radius Config=Learned ε2021.04 | — | 47.31 | |
| FocalBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 38.4 | |
| Focal LossBackbone=ResNet-322021.04 | — | 38.41 | |
| KCL†Backbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 42.8 | |
| LDAMBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 39.6 | |
| LDAM LossBackbone=ResNet-322021.04 | — | 39.6 | |
| LDAM-DRWBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 42 | |
| M2m-ERMBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 42.9 | |
| M2m-LDAMBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 43.5 | |
| ReSampleBackbone=ResNet-322021.04 | — | 33.44 | |
| ReWeightBackbone=ResNet-322021.04 | — | 33.99 | |
| smDRAGONBackbone=ResNet-322021.04 | — | 43.55 | |
| SSLBackbone=ResNet-32, Reproduced=true2021.04 | — | 37.51 | |
| SSPBackbone=ResNet-322021.04 | — | 43.43 | |
| TSCBackbone=ResNet-32, Imbalance Ratio=1002021.11 | — | 43.8 | |
| τ-normBackbone=ResNet-32, Reproduced=true2021.04 | — | 41.11 |