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Models/GML (ResNet-32)

GML (ResNet-32)

Reported on 15 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.

Methodology9 results

Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-05-02
41.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-05-02
33
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-05-02
46
best: 10.9 (LPT)
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Long-tail LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2023-05-02
41.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Long-tail LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-05-02
33
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2023-05-02
46
best: 10.9 (LPT)
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2023-05-02
41.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-05-02
33
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2023-05-02
46
best: 10.9 (LPT)
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160

Computer Vision6 results

Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-05-02
41.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-05-02
33
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-05-02
46
best: 10.9 (LPT)
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-05-02
41.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-05-02
33
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-05-02
46
best: 10.9 (LPT)
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels arXiv:2305.01160