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PC

Reported on 17 benchmarks across 6 tasks · 2 papers

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· 2023-02-01
42.25
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-02-01
30.88
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-02-01
46.59
best: 10.9 (LPT)
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Long-tail LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2023-02-01
42.25
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Long-tail LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-02-01
30.88
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2023-02-01
46.59
best: 10.9 (LPT)
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2023-02-01
42.25
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-02-01
30.88
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2023-02-01
46.59
best: 10.9 (LPT)
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491

Computer Vision8 results

Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-02-01
42.25
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-02-01
30.88
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-02-01
46.59
best: 10.9 (LPT)
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-02-01
42.25
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-02-01
30.88
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2023-02-01
46.59
best: 10.9 (LPT)
Learning Prototype Classifiers for Long-Tailed Recognition arXiv:2302.00491
Image ClassificationonCUB-200-2011
Accuracy· 2017-05-22
86.9
best: 92.8 (PIM)
Pairwise Confusion for Fine-Grained Visual Classification arXiv:1705.08016
Fine-Grained Image ClassificationonCUB-200-2011
Accuracy· 2017-05-22
86.9
best: 92.8 (PIM)
Pairwise Confusion for Fine-Grained Visual Classification arXiv:1705.08016