CoACT

Reported on 6 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.

Methodology6 results

Continual Learningon CUB-200-2011
Last Accuracy · 2024-05-26
81.19
SOTA
Few-shot Tuning of Foundation Models for Class-incremental Learning arXiv:2405.16625
Continual Learningonmini-Imagenet
Last Accuracy · 2024-05-26
96.24
SOTA
Few-shot Tuning of Foundation Models for Class-incremental Learning arXiv:2405.16625
Class Incremental Learningon CUB-200-2011
Last Accuracy · 2024-05-26
81.19
SOTA
Few-shot Tuning of Foundation Models for Class-incremental Learning arXiv:2405.16625
Class Incremental Learningonmini-Imagenet
Last Accuracy · 2024-05-26
96.24
SOTA
Few-shot Tuning of Foundation Models for Class-incremental Learning arXiv:2405.16625
Continual LearningonCIFAR-100
Last Accuracy· 2024-05-26
84.63
best: 86.06 (PriViLege)
Few-shot Tuning of Foundation Models for Class-incremental Learning arXiv:2405.16625
Class Incremental LearningonCIFAR-100
Last Accuracy· 2024-05-26
84.63
best: 86.06 (PriViLege)
Few-shot Tuning of Foundation Models for Class-incremental Learning arXiv:2405.16625