| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| SUN397 | GLA | Accuracy83.4 | 49 | 21d ago | |
| SUN397 base-to-new | TCP+CAKI | Base Accuracy83.7 | 39 | 26d ago | |
| SUN 397 (test) | GLA | Top-1 Accuracy83.4 | 35 | 1mo ago | |
| Places-365 | VIC-MAE | Top-1 Acc60.7 | 28 | 21d ago | |
| SUN RGB-D Scene (test) | Finetuned ResNet101-RNN | Acc (RGB-D)60.7 | 25 | 3mo ago | |
| MIT indoor 67 (val) | FiGKD | Top-1 Accuracy68.43 | 24 | 2mo ago | |
| SUN 397 (val) | Accuracy78.93 | 19 | 3mo ago | ||
| Places365 15 Chunks | LoRA | AP32.49 | 18 | 15d ago | |
| MIT Indoor 67 | Semantic-Aware Scene Recognition | Top-1 Accuracy87.1 | 18 | 3mo ago | |
| MIT-67 (test) | CSRRM | Accuracy88.731 | 13 | 3mo ago | |
| SUN397 New classes | MMRL | Accuracy79.2 | 12 | 3mo ago | |
| SUN397 Base classes | MMRL | Accuracy83.23 | 12 | 3mo ago | |
| Places 205 | Top-1 Accuracy14.9 | 8 | 3mo ago | ||
| Taskonomy tiny (test) | Accuracy71 | 8 | 3mo ago | ||
| P-HVU | CMAP25.8 | 8 | 3mo ago | ||
| VEDB | AULC0.28 | 6 | 3mo ago | ||
| PLACES-LT ResNet-152 (test) | REPAIR | Hit@145.5 | 5 | 2mo ago | |
| Dynamic Scene | P3D ResNet | Accuracy94.6 | 5 | 3mo ago |
