Food-101
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Multimodal Multiclass Classification | FOOD-101 (test) | Accuracy94.6 | 45 | |
| Image Classification | Food-101 (test) | Accuracy87.23 | 36 | |
| Food Classification | Food-101 9 | Accuracy94.99 | 16 | |
| Visual Recognition | Food-101 | Top-1 Acc99.3 | 16 | |
| Knowledge Distillation | Food-101 (test) | Accuracy (k=1)35.8 | 15 | |
| Fine-grained Visual Categorization | Food-101 (test) | Accuracy98.6 | 15 | |
| Classification | UPMC Food-101 imbalance ratio r=100 (test) | Overall Accuracy20.22 | 13 | |
| Classification | UPMC Food-101 imbalance ratio r=20 (test) | Overall Accuracy34.81 | 13 | |
| Image Classification | Food-101 Full | Top-1 Accuracy90 | 12 | |
| Image Classification | Food-101 10 samples/class | Top-1 Accuracy82.5 | 12 | |
| Image Classification | Food-101 LT | Avg Class Recall49 | 12 | |
| Out-of-distribution Discovery | Food-101 | Discovery Rate95.9 | 11 | |
| Label Noise Detection | Food-101N (val) | Average Error Rate6.99 | 11 | |
| Image Classification | Food-101N r ≈ 20% (test) | Accuracy86.4 | 10 | |
| Label Noise Detection | Food-101N verified (val) | Error Rate6.99 | 10 | |
| Clustering | Food-101 | ARI0.478 | 9 | |
| Test-Time Adaptation | Food-101 (test) | iNaturalist Accuracy (S)88.35 | 8 | |
| Zero-shot classification | Food-101 | Mean Accuracy Delta-11.65 | 7 | |
| Out-of-Distribution Detection | Food-101N | AUROC97.7 | 7 | |
| Image Classification | Food-101 16K sequence length (test) | Train runtime (s)891 | 7 | |
| Image Classification | Food-101 all-to-all | Accuracy86.3 | 7 | |
| Out-of-Distribution Detection | Food-101 (test) | iNaturalist FPR951.31 | 7 | |
| Multimodal Classification | FOOD-101 Hard (test) | Accuracy93.4 | 7 | |
| Out-of-Distribution Retrieval | Food-101 OOD (test) | AR@190.6 | 6 | |
| Fine-grained retrieval | Food-101 (test) | Recall@195.4 | 6 |
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