Incremental Learning On Imagenet100 10 Steps
Metriken
# M Params
Average Incremental Accuracy
Average Incremental Accuracy Top-5
Final Accuracy
Final Accuracy Top-5
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | # M Params | Average Incremental Accuracy | Average Incremental Accuracy Top-5 | Final Accuracy | Final Accuracy Top-5 |
|---|---|---|---|---|---|
| resolving-task-confusion-in-dynamic-expansion | 116.54 | 77.66 | 94.17 | 67.34 | 88.84 |
| random-path-selection-for-incremental | - | - | 87.90 | - | 74.00 |
| large-scale-incremental-learning-1 | 11.22 | - | 90.60 | - | 84.40 |
| maintaining-discrimination-and-fairness-in | 11.22 | - | 91.00 | - | 84.10 |
| end-to-end-incremental-learning | 11.22 | - | 89.92 | - | 80.29 |
| dytox-transformers-for-continual-learning | 11.01 | 77.15 | 92.04 | 69.10 | 87.98 |
| der-dynamically-expandable-representation-for | - | 76.12 | 92.79 | 66.07 | 88.38 |
| icarl-incremental-classifier-and | 11.22 | - | 83.60 | - | 63.80 |
| der-dynamically-expandable-representation-for | 112.27 | 77.18 | 93.23 | 66.70 | 87.52 |
| foster-feature-boosting-and-compression-for | - | 77.75 | - | - | - |
| resolving-task-confusion-in-dynamic-expansion | 26.36 | 77.50 | 93.60 | 67.30 | 87.94 |
| revisiting-a-knn-based-image-classification | - | 85.1 | - | - | - |
| rmm-reinforced-memory-management-for-class-1 | - | 78.47 | - | - | - |