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SOTA
Long Tail Learning
Long Tail Learning On Imagenet Lt
Long Tail Learning On Imagenet Lt
평가 지표
Top-1 Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Top-1 Accuracy
Paper Title
Repository
BatchFormer(ResNet-50, RIDE)
55.7
BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning
Online Feature Augmentation
35.3
Feature Space Augmentation for Long-Tailed Data
-
BALMS
41.8
Balanced Meta-Softmax for Long-Tailed Visual Recognition
VL-LTR (ViT-B-16)
77.2
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition
APA (SE-ResNet-50)
57.9
Adaptive Parametric Activation
-
DeiT-LT
59.1
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed Datasets
ProCo (ResNeXt50)
58.0
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition
ProCo (ResNet50)
60.2
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition
cRT + SSP
51.3
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
KCL
51.5
Exploring Balanced Feature Spaces for Representation Learning
-
BALLAD(ResNet-101)
70.5
A Simple Long-Tailed Recognition Baseline via Vision-Language Model
BatchFormer(ResNet-50, PaCo)
57.4
BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning
NCL(ResNet-50)
57.4
Nested Collaborative Learning for Long-Tailed Visual Recognition
-
OPeN (ResNeXt-50)
55.1
Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images
TSC(ResNet-50)
52.4
Targeted Supervised Contrastive Learning for Long-Tailed Recognition
smDRAGON
42.0
From Generalized zero-shot learning to long-tail with class descriptors
RIDE (ResNeXt-50)
56.4
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts
DRO-LT
53.5
Distributional Robustness Loss for Long-tail Learning
-
LDAM + DRW + SAM
53.1
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data
LIFT (ViT-B/16)
78.3
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
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