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Models/IBLLoss

IBLLoss

Reported on 10 benchmarks across 5 tasks · 1 paper

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· 2021-10-06
12.93
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-10-06
61.52
best: 10.9 (LPT)
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Long-tail LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2021-10-06
12.93
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2021-10-06
61.52
best: 10.9 (LPT)
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Generalized Few-Shot LearningonCIFAR-10-LT (ρ=10)
Error Rate· 2021-10-06
12.93
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2021-10-06
61.52
best: 10.9 (LPT)
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444

Computer Vision4 results

Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2021-10-06
12.93
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-10-06
61.52
best: 10.9 (LPT)
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Few-Shot Image ClassificationonCIFAR-10-LT (ρ=10)
Error Rate· 2021-10-06
12.93
best: 5 (GLMC+MaxNorm (ResNet-34, channel x4))
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-10-06
61.52
best: 10.9 (LPT)
Influence-Balanced Loss for Imbalanced Visual Classification arXiv:2110.02444