Image Classification on Caltech256
83.65AccuracyEvoAug (Learned Clustering)
Evaluation results
| Method | Links | |
|---|---|---|
| EvoAug (Learned Clustering)Model=ResNet50, Evaluation Protocol=5-way, 1-shot2026.02 | 83.65 | |
| AutoAugmentModel=ResNet50, Evaluation Protocol=5-way, 1-shot2026.02 | 82.92 | |
| EvoAug (Learned Clustering)Model=ViT-Small, Evaluation Protocol=5-way, 1-shot2026.02 | 82.12 | |
| CLIP2026.04 | 82.04 | |
| FARE2026.04 | 81.97 | |
| RandAugmentModel=ResNet50, Evaluation Protocol=5-way, 1-shot2026.02 | 81.63 | |
| Random TreeModel=ResNet50, Evaluation Protocol=5-way, 1-shot2026.02 | 81.57 | |
| EvoAug (Learned Clustering)Model=MobileNet, Evaluation Protocol=5-way, 1-shot2026.02 | 80.09 | |
| NoOp / Classical TreeModel=ResNet50, Evaluation Protocol=5-way, 1-shot2026.02 | 78.67 | |
| PMG-AFT2026.04 | 78.43 | |
| TGA-ZSR2026.04 | 78.09 | |
| AdvFLYPfull2026.04 | 77.44 | |
| AdvFLYP2026.04 | 76.98 | |
| TeCoA2026.04 | 76.76 | |
| RandAugmentModel=ViT-Small, Evaluation Protocol=5-way, 1-shot2026.02 | 75.6 | |
| AutoAugmentModel=ViT-Small, Evaluation Protocol=5-way, 1-shot2026.02 | 75.38 | |
| RandAugmentModel=MobileNet, Evaluation Protocol=5-way, 1-shot2026.02 | 71.97 | |
| AutoAugmentModel=MobileNet, Evaluation Protocol=5-way, 1-shot2026.02 | 71.47 | |
| Naive BaselineModel=MobileNet, Evaluation Protocol=5-way, 1-shot2026.02 | 67.28 | |
| Naive BaselineModel=ViT-Small, Evaluation Protocol=5-way, 1-shot2026.02 | 66.72 | |
| Naive BaselineModel=ResNet50, Evaluation Protocol=5-way, 1-shot2026.02 | 65.77 |