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SOTA
Langschwanzlernen
Long Tail Learning On Cifar 10 Lt R 100
Long Tail Learning On Cifar 10 Lt R 100
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Error Rate
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Error Rate
Paper Title
ETF Classifier + DR (Resnet)
23.5
Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?
LDAM-DRW
22.97
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
LDAM-DRW + SSP
22.17
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
ELP
22
A Simple Episodic Linear Probe Improves Visual Recognition in the Wild
TSC(ResNet-32)
21.3
Targeted Supervised Contrastive Learning for Long-Tailed Recognition
CE+DRS+GIT
21.24
Do Deep Networks Transfer Invariances Across Classes?
smDRAGON
20.37
From Generalized zero-shot learning to long-tail with class descriptors
TLC (4 experts)
19.6
Trustworthy Long-Tailed Classification
MetaSAug-LDAM
19.34
MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition
ACE (4 experts)
18.6
ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot
MiSLAS
17.9
Improving Calibration for Long-Tailed Recognition
VS + SAM
17.6
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data
FBL (ResNet-32)
17.54
Feature-Balanced Loss for Long-Tailed Visual Recognition
GCL
17.32
Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment
DirMixE
16.74
Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition
TADE
16.2
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition
NCL* + WGCC (ensemble)
15.4
Weight-guided class complementing for long-tailed image recognition
NCL(ResNet32)
15.3
Nested Collaborative Learning for Long-Tailed Visual Recognition
SimSiam+rwSAM
14.4
Self-supervised Learning is More Robust to Dataset Imbalance
ConCutMix
13.93
Enhanced Long-Tailed Recognition with Contrastive CutMix Augmentation
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