Long Tail Learning On Cifar 10 Lt R 10

評価指標

Error Rate

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名	Error Rate	Paper Title	Repository
ResCom	8.0	Rebalanced Siamese Contrastive Mining for Long-Tailed Recognition
TADE	9.2	Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition	-
GLMC+MaxNorm (ResNet-34, channel x4)	5	Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions
GCLLoss	10.77	Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment
KCL	12.00	Exploring Balanced Feature Spaces for Representation Learning	-
ViT-B + Bal-BCE	8.7	Learning Imbalanced Data with Vision Transformers
MetaSAug-LDAM	10.32	MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition
LDAM-DRW + SSP	11.47	Rethinking the Value of Labels for Improving Class-Imbalanced Learning
ELF&LDAM+DRW	12.00	ELF: An Early-Exiting Framework for Long-Tailed Classification	-
ELP	11.3	A Simple Episodic Linear Probe Improves Visual Recognition in the Wild
Causal Norm	11.5	Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
ViT-B + CB	10.1	Learning Imbalanced Data with Vision Transformers
MiSLAS	10	Improving Calibration for Long-Tailed Recognition
Prior-LT	12.20	Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective
SAFA+LDAM-DRW (ResNeXt-29)	10.61	SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification	-
Empirical Risk Minimization (ERM, CE)	13.61	Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
M2m	12.5	M2m: Imbalanced Classification via Major-to-minor Translation
UniMix+Bayias	10.34	Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective
VS + ADRW + TLA	8.18	A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning. paper with code
LWS	8.9	Decoupling Representation and Classifier for Long-Tailed Recognition

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