Long-tail Learning

Long-tailed learning, one of the most challenging problems in visual recognition, aims to train well-performing models from a large number of images that follow a long-tailed class distribution.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–125 of 131 papers

Title	Date	Tasks	Status
Supervised Contrastive Learning on Blended Images for Long-tailed Recognition	Nov 22, 2022	Contrastive LearningData Augmentation	—Unverified
SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification	Nov 6, 2022	image-classificationImage Classification	—Unverified
A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems	Sep 15, 2022	Domain GeneralizationFine-Grained Image Classification	CodeCode Available
Bag of Tricks for Long-Tail Visual Recognition of Animal Species in Camera-Trap Images	Jun 24, 2022	ClassificationLong-tail Learning	CodeCode Available
Long-tailed Recognition by Learning from Latent Categories	Jun 2, 2022	Data AugmentationDiversity	—Unverified
ELM: Embedding and Logit Margins for Long-Tail Learning	Apr 27, 2022	Contrastive LearningLong-tail Learning	—Unverified
Rebalanced Siamese Contrastive Mining for Long-Tailed Recognition	Mar 22, 2022	Contrastive LearningLong-tail Learning	CodeCode Available
Long-Tailed Classification with Gradual Balanced Loss and Adaptive Feature Generation	Feb 28, 2022	Long-tail Learning	—Unverified
Retrieval Augmented Classification for Long-Tail Visual Recognition	Feb 22, 2022	Classificationimage-classification	—Unverified
Balancing Domain Experts for Long-Tailed Camera-Trap Recognition	Feb 15, 2022	Long-tail LearningOptical Flow Estimation	—Unverified
Improving Tail-Class Representation with Centroid Contrastive Learning	Oct 19, 2021	Contrastive Learningimage-classification	—Unverified
Optimal Transport for Long-Tailed Recognition with Learnable Cost Matrix	Sep 29, 2021	Long-tail Learning	—Unverified
Fairness-aware Class Imbalanced Learning	Sep 21, 2021	FairnessLong-tail Learning	—Unverified
ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot	Aug 5, 2021	Long-tail Learning	CodeCode Available
Long-Tailed Multi-Label Visual Recognition by Collaborative Training on Uniform and Re-Balanced Samplings	Jun 19, 2021	Long-tail Learning	—Unverified
Distributional Robustness Loss for Long-tail Learning	Apr 7, 2021	Long-tail Learning	—Unverified
Distilling Virtual Examples for Long-tailed Recognition	Mar 28, 2021	Knowledge DistillationLong-tail Learning	CodeCode Available
Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification	Mar 26, 2021	ClassificationContrastive Learning	—Unverified
Exploring Balanced Feature Spaces for Representation Learning	Jan 1, 2021	Contrastive LearningLong-tail Learning	—Unverified
BLT: Balancing Long-Tailed Datasets with Adversarially-Perturbed Images	Oct 30, 2020	Data AugmentationImage Generation	CodeCode Available
Posterior Re-calibration for Imbalanced Datasets	Oct 22, 2020	Long-tail LearningSemantic Segmentation	CodeCode Available
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data with Diversity In Memory	Aug 22, 2020	Data AugmentationDiversity	—Unverified
AlphaNet: Improving Long-Tail Classification By Combining Classifiers	Aug 17, 2020	ClassificationLong-tail Learning	CodeCode Available
Feature Space Augmentation for Long-Tailed Data	Aug 9, 2020	Image ClassificationLong-tail Learning	—Unverified
ELF: An Early-Exiting Framework for Long-Tailed Classification	Jun 22, 2020	ClassificationGeneral Classification	—Unverified

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All datasets ImageNet-LT CIFAR-100-LT (ρ=100)CIFAR-10-LT (ρ=10)iNaturalist 2018 CIFAR-100-LT (ρ=10)Places-LT CIFAR-10-LT (ρ=100)CIFAR-100-LT (ρ=50)MIMIC-CXR-LT NIH-CXR-LT COCO-MLT VOC-MLT

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	LIFT (ViT-L/14)	Top-1 Accuracy	82.9	—	Unverified
2	µ2Net+ (ViT-L/16)	Top-1 Accuracy	82.5	—	Unverified
3	MAM (ViT-B/16)	Top-1 Accuracy	82.3	—	Unverified
4	LIFT (ViT-B/16)	Top-1 Accuracy	78.3	—	Unverified
5	VL-LTR (ViT-B-16)	Top-1 Accuracy	77.2	—	Unverified
6	BALLAD(ResNet-50×16)	Top-1 Accuracy	76.5	—	Unverified
7	BALLAD(ViT-B-16)	Top-1 Accuracy	75.7	—	Unverified
8	BALLAD(ResNet-101)	Top-1 Accuracy	70.5	—	Unverified
9	VL-LTR (ResNet-50)	Top-1 Accuracy	70.1	—	Unverified
10	BALLAD(ResNet-50)	Top-1 Accuracy	67.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Cross-Entropy (CE)	Error Rate	62.75	—	Unverified
2	Cross-Entropy (CE)	Error Rate	61.68	—	Unverified
3	IBLLoss	Error Rate	61.52	—	Unverified
4	Cross-Entropy + Curvature Regularization	Error Rate	59.5	—	Unverified
5	CE-DRW	Error Rate	58.9	—	Unverified
6	LDAM-DRW	Error Rate	57.96	—	Unverified
7	ELP	Error Rate	57.6	—	Unverified
8	CDB-loss	Error Rate	57.43	—	Unverified
9	CE-DRW-IC	Error Rate	56.9	—	Unverified
10	LDAM-DRW + SSP	Error Rate	56.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RISDA	Error Rate	20.11	—	Unverified
2	Empirical Risk Minimization (ERM, CE)	Error Rate	13.61	—	Unverified
3	Class-balanced Reweighting	Error Rate	13.46	—	Unverified
4	Class-balanced Resampling	Error Rate	13.21	—	Unverified
5	IBLLoss	Error Rate	12.93	—	Unverified
6	Class-balanced Focal Loss	Error Rate	12.9	—	Unverified
7	DecTDE	Error Rate	12.63	—	Unverified
8	M2m	Error Rate	12.5	—	Unverified
9	Prior-LT	Error Rate	12.2	—	Unverified
10	ELF&LDAM+DRW	Error Rate	12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LIFT (ViT-L/14@336px)	Top-1 Accuracy	87.4	—	Unverified
2	LIFT (ViT-L/14)	Top-1 Accuracy	85.2	—	Unverified
3	GML (ViT-B-16)	Top-1 Accuracy	82.1	—	Unverified
4	LIFT (ViT-B/16)	Top-1 Accuracy	80.4	—	Unverified
5	RAC (ViT-B-16)	Top-1 Accuracy	80.24	—	Unverified
6	GPaCo (2-R152)	Top-1 Accuracy	79.8	—	Unverified
7	TADE(ResNet-152)	Top-1 Accuracy	77	—	Unverified
8	ProCo (ResNet50)	Top-1 Accuracy	75.8	—	Unverified
9	MDCS(Resnet50)	Top-1 Accuracy	75.6	—	Unverified
10	DeiT-LT	Top-1 Accuracy	75.1	—	Unverified