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Models/C-FSCIL

C-FSCIL

Reported on 8 benchmarks across 2 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology8 results

Continual Learningonmini-Imagenet
Average Accuracy· 2022-03-30
61.61
best: 95.27 (PriViLege)
SOTA
Constrained Few-shot Class-incremental Learning arXiv:2203.16588
Continual Learningonmini-Imagenet
Last Accuracy · 2022-03-30
51.41
best: 96.24 (CoACT)
SOTA
Constrained Few-shot Class-incremental Learning arXiv:2203.16588
Class Incremental Learningonmini-Imagenet
Average Accuracy· 2022-03-30
61.61
best: 95.27 (PriViLege)
SOTA
Constrained Few-shot Class-incremental Learning arXiv:2203.16588
Class Incremental Learningonmini-Imagenet
Last Accuracy · 2022-03-30
51.41
best: 96.24 (CoACT)
SOTA
Constrained Few-shot Class-incremental Learning arXiv:2203.16588
Continual LearningonCIFAR-100
Average Accuracy· 2022-03-30
61.67
best: 88.08 (PriViLege)
Constrained Few-shot Class-incremental Learning arXiv:2203.16588
Continual LearningonCIFAR-100
Last Accuracy· 2022-03-30
50.47
best: 86.06 (PriViLege)
Constrained Few-shot Class-incremental Learning arXiv:2203.16588
Class Incremental LearningonCIFAR-100
Average Accuracy· 2022-03-30
61.67
best: 88.08 (PriViLege)
Constrained Few-shot Class-incremental Learning arXiv:2203.16588
Class Incremental LearningonCIFAR-100
Last Accuracy· 2022-03-30
50.47
best: 86.06 (PriViLege)
Constrained Few-shot Class-incremental Learning arXiv:2203.16588