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 101–131 of 131 papers

Title	Date	Tasks	Status	Hype
Exploring Balanced Feature Spaces for Representation Learning	Jan 1, 2021	Contrastive LearningLong-tail Learning	—Unverified	0
Disentangling Label Distribution for Long-tailed Visual Recognition	Dec 1, 2020	Image ClassificationLong-tail Learning	CodeCode Available	1
BLT: Balancing Long-Tailed Datasets with Adversarially-Perturbed Images	Oct 30, 2020	Data AugmentationImage Generation	CodeCode Available	0
Posterior Re-calibration for Imbalanced Datasets	Oct 22, 2020	Long-tail LearningSemantic Segmentation	CodeCode Available	0
Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance	Oct 5, 2020	Long-tail Learning	CodeCode Available	1
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts	Oct 5, 2020	DiversityImage Classification	CodeCode Available	1
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect	Sep 28, 2020	Causal Inferencecounterfactual	CodeCode Available	1
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data with Diversity In Memory	Aug 22, 2020	Data AugmentationDiversity	—Unverified	0
AlphaNet: Improving Long-Tail Classification By Combining Classifiers	Aug 17, 2020	ClassificationLong-tail Learning	CodeCode Available	0
Feature Space Augmentation for Long-Tailed Data	Aug 9, 2020	Image ClassificationLong-tail Learning	—Unverified	0
Balanced Meta-Softmax for Long-Tailed Visual Recognition	Jul 21, 2020	General ClassificationInstance Segmentation	CodeCode Available	1
Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets	Jul 19, 2020	Binary ClassificationGeneral Classification	CodeCode Available	1
Long-tail learning via logit adjustment	Jul 14, 2020	Long-tail Learning	CodeCode Available	1
ELF: An Early-Exiting Framework for Long-Tailed Classification	Jun 22, 2020	ClassificationGeneral Classification	—Unverified	0
Rethinking the Value of Labels for Improving Class-Imbalanced Learning	Jun 13, 2020	Long-tail Learning	CodeCode Available	1
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition	Jun 1, 2020	Few-Shot LearningLong-tail Learning	—Unverified	0
Large-Scale Object Detection in the Wild from Imbalanced Multi-Labels	May 18, 2020	Long-tail LearningObject	—Unverified	0
Long-Tailed Recognition Using Class-Balanced Experts	Apr 7, 2020	Long-tail Learning	CodeCode Available	0
From Generalized zero-shot learning to long-tail with class descriptors	Apr 5, 2020	Few-Shot LearningGeneralized Few-Shot Learning	CodeCode Available	1
M2m: Imbalanced Classification via Major-to-minor Translation	Apr 1, 2020	ClassificationDiversity	CodeCode Available	1
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective	Mar 24, 2020	Domain AdaptationLong-tail Learning	CodeCode Available	1
Equalization Loss for Long-Tailed Object Recognition	Mar 11, 2020	Long-tail LearningObject	CodeCode Available	1
Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification	Jan 6, 2020	General ClassificationKnowledge Distillation	CodeCode Available	1
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition	Dec 5, 2019	Long-tail LearningRepresentation Learning	CodeCode Available	0
Decoupling Representation and Classifier for Long-Tailed Recognition	Oct 21, 2019	ClassificationGeneral Classification	CodeCode Available	1
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss	Jun 18, 2019	Long-tail LearningLong-tail learning with class descriptors	CodeCode Available	1
Large-Scale Long-Tailed Recognition in an Open World	Apr 10, 2019	ClassificationFew-Shot Learning	CodeCode Available	1
Multi-Label Image Recognition with Graph Convolutional Networks	Apr 7, 2019	Long-tail LearningMulti-Label Classification	CodeCode Available	0
Class-Balanced Loss Based on Effective Number of Samples	Jan 16, 2019	Image ClassificationLong-tail Learning	CodeCode Available	1
Focal Loss for Dense Object Detection	Aug 7, 2017	2D Object DetectionDense Object Detection	CodeCode Available	2
Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks	Dec 18, 2015	General ClassificationLong-tail Learning	CodeCode Available	0

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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