Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/CBD+TailCalibX

CBD+TailCalibX

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· 2021-11-10
49.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2021-11-10
38.87
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-11-10
53.41
best: 10.9 (LPT)
Feature Generation for Long-tail Classification arXiv:2111.05956
Long-tail LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2021-11-10
49.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Long-tail LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2021-11-10
38.87
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2021-11-10
53.41
best: 10.9 (LPT)
Feature Generation for Long-tail Classification arXiv:2111.05956
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2021-11-10
49.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2021-11-10
38.87
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· 2021-11-10
53.41
best: 10.9 (LPT)
Feature Generation for Long-tail Classification arXiv:2111.05956

Computer Vision6 results

Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2021-11-10
49.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2021-11-10
38.87
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-11-10
53.41
best: 10.9 (LPT)
Feature Generation for Long-tail Classification arXiv:2111.05956
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2021-11-10
49.1
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2021-11-10
38.87
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Feature Generation for Long-tail Classification arXiv:2111.05956
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· 2021-11-10
53.41
best: 10.9 (LPT)
Feature Generation for Long-tail Classification arXiv:2111.05956