Continual Learning On Sketch Fine Grained 6
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | Accuracy | Paper Title | Repository |
---|---|---|---|
H$^{2}$ | 76.2 | Helpful or Harmful: Inter-Task Association in Continual Learning | |
CondConvContinual | 80.77 | EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNING | |
PackNet | 76.17 | PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning | |
CPG | 80.33 | Compacting, Picking and Growing for Unforgetting Continual Learning | |
ProgressiveNet | 76.35 | Progressive Neural Networks | |
Piggyback | 79.91 | Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights |
0 of 6 row(s) selected.