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Models/cRT

cRT

Reported on 10 benchmarks across 5 tasks · 2 papers · 5 SOTA

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

Methodology6 results

Generalized Few-Shot ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2019-10-21
9
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Decoupling Representation and Classifier for Long-Tailed Recognition arXiv:1910.09217
Long-tail LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2019-10-21
9
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Decoupling Representation and Classifier for Long-Tailed Recognition arXiv:1910.09217
Generalized Few-Shot LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2019-10-21
9
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Decoupling Representation and Classifier for Long-Tailed Recognition arXiv:1910.09217
Generalized Few-Shot ClassificationonImageNet-GLT
Accuracy· 2022-07-19
37.57
best: 45.64 (RIDE + IFL)
Invariant Feature Learning for Generalized Long-Tailed Classification arXiv:2207.09504
Long-tail LearningonImageNet-GLT
Accuracy· 2022-07-19
37.57
best: 45.64 (RIDE + IFL)
Invariant Feature Learning for Generalized Long-Tailed Classification arXiv:2207.09504
Generalized Few-Shot LearningonImageNet-GLT
Accuracy· 2022-07-19
37.57
best: 45.64 (RIDE + IFL)
Invariant Feature Learning for Generalized Long-Tailed Classification arXiv:2207.09504

Computer Vision4 results

Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2019-10-21
9
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Decoupling Representation and Classifier for Long-Tailed Recognition arXiv:1910.09217
Few-Shot Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2019-10-21
9
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
Decoupling Representation and Classifier for Long-Tailed Recognition arXiv:1910.09217
Image ClassificationonImageNet-GLT
Accuracy· 2022-07-19
37.57
best: 45.64 (RIDE + IFL)
Invariant Feature Learning for Generalized Long-Tailed Classification arXiv:2207.09504
Few-Shot Image ClassificationonImageNet-GLT
Accuracy· 2022-07-19
37.57
best: 45.64 (RIDE + IFL)
Invariant Feature Learning for Generalized Long-Tailed Classification arXiv:2207.09504