Image Classification on Tiny ImageNet 200 class (test)
87.2Top-1 AccuracySS-CA
Evaluation Results
| Method | Links | |
|---|---|---|
| SS-CABackbone=ViT, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 87.2 | |
| Chen et al.Backbone=ViT, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 86.83 | |
| Xiao et al.Backbone=ViT, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 86.69 | |
| Conventional TrainingBackbone=ViT, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 86.68 | |
| SS-CABackbone=ResNet-101, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 75.94 | |
| Chen et al.Backbone=ResNet-101, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 75.7 | |
| Conventional TrainingBackbone=ResNet-101, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 75.67 | |
| Xiao et al.Backbone=ResNet-101, Evaluation Protocol=End-to-End Fine-Tuning2025.11 | 75.57 | |
| SS-CABackbone=CLIP (ViT/32b), Evaluation Protocol=Linear Probing2025.11 | 74.42 | |
| Chen et al.Backbone=CLIP (ViT/32b), Evaluation Protocol=Linear Probing2025.11 | 73.8 | |
| Xiao et al.Backbone=CLIP (ViT/32b), Evaluation Protocol=Linear Probing2025.11 | 73.4 | |
| Conventional TrainingBackbone=CLIP (ViT/32b), Evaluation Protocol=Linear Probing2025.11 | 73.31 | |
| BPLoss Function=CE2026.05 | 39.9 | |
| BPLoss Function=MSE2026.05 | 36 | |
| SBD ExpLoss Function=CE, Score Expansion=true2026.05 | 31.4 | |
| SBDLoss Function=CE, Score Expansion=false2026.05 | 28.3 | |
| EBDLoss Function=MSE2026.05 | 18.5 | |
| DFALoss Function=CE2026.05 | 17.5 |