Papers with Code · CC BY-SA 4.0

CIFAR-100-LT (ρ=10)

아카이브 평가 31건 · 마지막 적재/변경 2026-10-30

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

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원본 기록 순서 · 순위 미부여
모델	원본 지표·값	논문	구현
LIFT (ViT-B/16, ImageNet-21K pre-training)	Error Rate 8.7	Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts 2023-09-18	코드 1
LPT	Error Rate 9	LPT: Long-tailed Prompt Tuning for Image Classification 2022-10-03	코드 1
VPT	Error Rate 10.4	Visual Prompt Tuning 2022-03-23	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6
LIFT (ViT-B/16, CLIP)	Error Rate 15.1	Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts 2023-09-18	코드 1
GLMC+MaxNorm (ResNet-32, channel x4)	Error Rate 25.72	Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions 2023-05-15	코드 1 · 코드 2
GLMC (ResNet-34, channel x4)	Error Rate 26.53	Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions 2023-05-15	코드 1 · 코드 2
SURE(ResNet-32)	Error Rate 26.76	SURE: SUrvey REcipes for building reliable and robust deep networks 2024-03-01	코드 1
PC	Error Rate 30.88	Learning Prototype Classifiers for Long-Tailed Recognition 2023-02-01	코드 1
LTR-weight-balancing	Error Rate 31.33	Long-Tailed Recognition via Weight Balancing 2022-03-27	코드 1 · 코드 2
GML (ResNet-32)	Error Rate 33.0	Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels 2023-05-02	코드 1
VS + ADRW + TLA	Error Rate 34.41	A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning. paper with code 2023-10-07	코드 1
Difficulty-Net	Error Rate 34.78	Difficulty-Net: Learning to Predict Difficulty for Long-Tailed Recognition 2022-09-07	코드 1
BCL+CUDA	Error Rate 35.4	CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition 2023-02-10	코드 1
GLAG	Error Rate 35.5	Long-Tailed Classification with Gradual Balanced Loss and Adaptive Feature Generation 2022-02-28	연결 없음
LCReg	Error Rate 35.8	Long-tailed Recognition by Learning from Latent Categories 2022-06-02	연결 없음
TADE	Error Rate 36.4	Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition 2021-07-20	코드 1 · 코드 2
DRO-LT	Error Rate 36.59	Distributional Robustness Loss for Long-tail Learning 2021-04-07	연결 없음
MiSLAS	Error Rate 36.8	Improving Calibration for Long-Tailed Recognition 2021-04-01	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
SMC	Error Rate 37.5	Supervised Contrastive Learning on Blended Images for Long-tailed Recognition 2022-11-22	연결 없음
Hybrid-PSC	Error Rate 37.63	Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification 2021-03-26	연결 없음
LADE	Error Rate 38.3	Disentangling Label Distribution for Long-tailed Visual Recognition 2020-12-01	코드 1 · 코드 2
RIDE + CMO + Curvature Regularization	Error Rate 38.60	Predicting and Enhancing the Fairness of DNNs with the Curvature of Perceptual Manifolds 2023-03-22	코드 1 · 코드 2
MetaSAug-LDAM	Error Rate 38.72	MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition 2021-03-23	코드 1
UniMix+Bayias (ResNet-32)	Error Rate 38.75	Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective 2021-11-06	코드 1
CBD+TailCalibX	Error Rate 38.87	Feature Generation for Long-tail Classification 2021-11-10	코드 1
ELP	Error Rate 40.9	A Simple Episodic Linear Probe Improves Visual Recognition in the Wild 2022-01-01	코드 1 · 코드 2
LDAM-DRW + SSP	Error Rate 41.09	Rethinking the Value of Labels for Improving Class-Imbalanced Learning 2020-06-13	코드 1
smDRAGON	Error Rate 41.23	From Generalized zero-shot learning to long-tail with class descriptors 2020-04-05	코드 1
CDB-loss	Error Rate 41.26	Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance 2020-10-05	코드 1
LDAM-DRW	Error Rate 41.29	Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss 2019-06-18	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7