Incremental Learning On Imagenet 10 Steps
Metrics
# M Params
Average Incremental Accuracy
Average Incremental Accuracy Top-5
Final Accuracy
Final Accuracy Top-5
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | # M Params | Average Incremental Accuracy | Average Incremental Accuracy Top-5 | Final Accuracy | Final Accuracy Top-5 |
|---|---|---|---|---|---|
| der-dynamically-expandable-representation-for | 116.89 | 68.84 | 88.17 | 60.16 | 82.86 |
| dytox-transformers-for-continual-learning | 11.36 | 71.29 | 88.59 | 63.34 | 84.49 |
| end-to-end-incremental-learning | 11.68 | - | 72.09 | - | 52.29 |
| maintaining-discrimination-and-fairness-in | 11.68 | 65.67 | 86.60 | 55.60 | 81.10 |
| der-dynamically-expandable-representation-for | - | 66.73 | 87.08 | 58.62 | 81.89 |
| rmm-reinforced-memory-management-for-class-1 | - | 67.45 | - | - | - |
| large-scale-incremental-learning-1 | 11.68 | - | 84.00 | - | 73.20 |
| foster-feature-boosting-and-compression-for | - | 68.34 | - | - | - |
| revisiting-a-knn-based-image-classification | - | 85.5 | - | - | - |
| icarl-incremental-classifier-and | 11.68 | 38.40 | 63.70 | 22.70 | 44.00 |