14.1.5.2.1 Long Tailed Data Analysis

Chapter Contents (Back)
Imbalanced Data. Long-Tailed Data. Learning.
See also Long-Tailed Object Detection.

Sinha, S.[Saptarshi], Ohashi, H.[Hiroki], Nakamura, K.[Katsuyuki],
Class-Difficulty Based Methods for Long-Tailed Visual Recognition,
IJCV(130), No. 10, October 2022, pp. 2517-2531.
Springer DOI 2209
BibRef
Earlier:
Class-wise Difficulty-balanced Loss for Solving Class-imbalance,
ACCV20(VI:549-565).
Springer DOI 2103
BibRef

Sinha, S.[Saptarshi], Ohashi, H.[Hiroki],
Difficulty-Net: Learning to Predict Difficulty for Long-Tailed Recognition,
WACV23(6433-6442)
IEEE DOI 2302
Training, Codes, Tail, Predictive models, Algorithms: Machine learning architectures, formulations, ethical computer vision BibRef

Wang, W.Q.[Wei-Qiu], Zhao, Z.C.[Zhi-Cheng], Wang, P.[Pingyu], Su, F.[Fei], Meng, H.Y.[Hong-Ying],
Attentive Feature Augmentation for Long-Tailed Visual Recognition,
CirSysVideo(32), No. 9, September 2022, pp. 5803-5816.
IEEE DOI 2209
Visualization, Head, Image recognition, Task analysis, Feature extraction, Data models, Training, Image classification, data synthesizing BibRef

Zhang, M.L.[Ming-Liang], Zhang, X.Y.[Xu-Yao], Wang, C.[Chuang], Liu, C.L.[Cheng-Lin],
Towards prior gap and representation gap for long-tailed recognition,
PR(133), 2023, pp. 109012.
Elsevier DOI 2210
Long-tailed learning, Prior gap, Representation gap, Image recognition BibRef

Liu, J.H.[Jia-Hang], Feng, R.[Ruilei], Chen, P.[Peng], Wang, X.Z.[Xiao-Zhen], Ni, Y.[Yue],
Dynamic Loss Reweighting Method Based on Cumulative Classification Scores for Long-Tailed Remote Sensing Image Classification,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Cui, J.Q.[Jie-Quan], Liu, S.[Shu], Tian, Z.T.[Zhuo-Tao], Zhong, Z.S.[Zhi-Sheng], Jia, J.Y.[Jia-Ya],
ResLT: Residual Learning for Long-Tailed Recognition,
PAMI(45), No. 3, March 2023, pp. 3695-3706.
IEEE DOI 2302
Tail, Head, Training, Magnetic heads, Image recognition, Transfer learning, Representation learning, Residual learning, long-tailed recognition BibRef

Zhao, X.Q.[Xin-Qiao], Xiao, J.[Jimin], Yu, S.Y.[Si-Yue], Li, H.[Hui], Zhang, B.F.[Bing-Feng],
Weight-guided class complementing for long-tailed image recognition,
PR(138), 2023, pp. 109374.
Elsevier DOI 2303
Image recognition, Long-tailed distribution, Gradient shift, Weight-guided method BibRef

Li, M.K.[Meng-Ke], Cheung, Y.M.[Yiu-Ming], Hu, Z.K.[Zhi-Kai],
Key Point Sensitive Loss for Long-Tailed Visual Recognition,
PAMI(45), No. 4, April 2023, pp. 4812-4825.
IEEE DOI 2303
Tail, Training, Head, Optimization, Visualization, Magnetic heads, Training data, Long-tailed classification, imbalance learning BibRef

Tiong, A.M.H.[Anthony Meng Huat], Li, J.[Junnan], Lin, G.S.[Guo-Sheng], Li, B.Y.[Bo-Yang], Xiong, C.M.[Cai-Ming], Hoi, S.C.H.[Steven C.H.],
Improving Tail-Class Representation with Centroid Contrastive Learning,
PRL(168), 2023, pp. 123-130.
Elsevier DOI 2304
Long-tailed classification, Imbalanced learning, Contrastive learning, Deep learning BibRef

Xiang, L.[Liuyu], Han, J.G.[Jun-Gong], Ding, G.[Guiguang],
Margin-aware rectified augmentation for long-tailed recognition,
PR(141), 2023, pp. 109608.
Elsevier DOI 2306
Long-tailed recognition, Data augmentation, Mixup BibRef

Guan, Q.J.[Qing-Ji], Li, Z.Z.[Zhuang-Zhuang], Zhang, J.[Jiayu], Huang, Y.P.[Ya-Ping], Zhao, Y.[Yao],
Joint representation and classifier learning for long-tailed image classification,
IVC(137), 2023, pp. 104759.
Elsevier DOI 2309
Long-tailed image classification, Representation learning, Classifier learning, Supervised contrastive learning BibRef

Kim, D.J.[Dong-Jin], Ke, T.W.[Tsung-Wei], Yu, S.X.[Stella X.],
Local pseudo-attributes for long-tailed recognition,
PRL(172), 2023, pp. 51-57.
Elsevier DOI 2309
Long-tailed recognition, Pseudo-attributes, Self-supervised learning BibRef

Zhang, Y.F.[Yi-Fan], Kang, B.Y.[Bing-Yi], Hooi, B.[Bryan], Yan, S.C.[Shui-Cheng], Feng, J.S.[Jia-Shi],
Deep Long-Tailed Learning: A Survey,
PAMI(45), No. 9, September 2023, pp. 10795-10816.
IEEE DOI 2309
Survey, Long-Tailed. BibRef

Zhou, X.S.[Xue-Song], Zhai, J.H.[Jun-Hai], Cao, Y.[Yang],
Feature fusion network for long-tailed visual recognition,
PR(144), 2023, pp. 109827.
Elsevier DOI 2310
Long-tailed learning, Head and tail classes, Feature representations, Feature fusion network BibRef

Liu, W.[Weide], Wu, Z.H.[Zhong-Hua], Wang, Y.M.[Yi-Ming], Ding, H.H.[Heng-Hui], Liu, F.[Fayao], Lin, J.[Jie], Lin, G.S.[Guo-Sheng],
LCReg: Long-tailed image classification with Latent Categories based Recognition,
PR(145), 2024, pp. 109971.
Elsevier DOI 2311
Long-tailed, Image classification, Latent Categories BibRef

Zhao, W.[Wei], Zhao, H.[Hong],
Hierarchical long-tailed classification based on multi-granularity knowledge transfer driven by multi-scale feature fusion,
PR(145), 2024, pp. 109842.
Elsevier DOI 2311
Long-tailed learning, Hierarchical classification, Multi-granularity, Multi-scale feature fusion, Knowledge transfer BibRef

Alexandridis, K.P.[Konstantinos Panagiotis], Luo, S.[Shan], Nguyen, A.[Anh], Deng, J.K.[Jian-Kang], Zafeiriou, S.[Stefanos],
Inverse Image Frequency for Long-Tailed Image Recognition,
IP(32), 2023, pp. 5721-5736.
IEEE DOI Code:
WWW Link. 2311
BibRef

Tan, Z.C.[Zi-Chang], Li, J.[Jun], Du, J.H.[Jin-Hao], Wan, J.[Jun], Lei, Z.[Zhen], Guo, G.D.[Guo-Dong],
NCL++: Nested Collaborative Learning for long-tailed visual recognition,
PR(147), 2024, pp. 110064.
Elsevier DOI 2312
BibRef
Earlier: A2, A1, A4, A5, A6, Only:
Nested Collaborative Learning for Long-Tailed Visual Recognition,
CVPR22(6939-6948)
IEEE DOI 2210
Long-tailed visual recognition, Collaborative learning, Online distillation, Deep learning. Training, Representation learning, Visualization, Uncertainty, Codes, Supervised learning, Transfer/low-shot/long-tail learning, retrieval BibRef

Baik, J.S.[Jae Soon], Yoon, I.Y.[In Young], Choi, J.W.[Jun Won],
DBN-Mix: Training dual branch network using bilateral mixup augmentation for long-tailed visual recognition,
PR(147), 2024, pp. 110107.
Elsevier DOI 2312
Long-tailed visual recognition, Class imbalance, Image classification, Mixup augmentation, Temperature scaling BibRef

Du, Y.J.[Ying-Jun], Sun, H.L.[Hao-Liang], Zhen, X.T.[Xian-Tong], Xu, J.[Jun], Yin, Y.L.[Yi-Long], Shao, L.[Ling], Snoek, C.G.M.[Cees G. M.],
MetaKernel: Learning Variational Random Features With Limited Labels,
PAMI(46), No. 3, March 2024, pp. 1464-1478.
IEEE DOI 2402
Task analysis, Kernel, Adaptation models, Prototypes, Optimization, Neural networks, Memory modules, Meta learning, few-shot learning, random features BibRef

Du, Y.J.[Ying-Jun], Shen, J.Y.[Jia-Yi], Zhen, X.T.[Xian-Tong], Snoek, C.G.M.[Cees G. M.],
SuperDisco: Super-Class Discovery Improves Visual Recognition for the Long-Tail,
CVPR23(19944-19954)
IEEE DOI 2309
BibRef

Xu, Z.Z.[Zheng-Zhuo], Chai, Z.H.[Zeng-Hao], Xu, C.Y.[Cheng-Yin], Yuan, C.[Chun], Yang, H.Q.[Hai-Qin],
Towards Effective Collaborative Learning in Long-Tailed Recognition,
MultMed(26), 2024, pp. 3754-3764.
IEEE DOI 2402
Tail, Federated learning, Task analysis, Uncertainty, Training, Head, Feature extraction, Image classification, long tail recognition, knowledge distillation BibRef

Ma, Y.B.[Yan-Biao], Jiao, L.C.[Li-Cheng], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan], Liu, X.[Xu], Chen, P.[Puhua],
Feature Distribution Representation Learning Based on Knowledge Transfer for Long-Tailed Classification,
MultMed(26), 2024, pp. 2772-2784.
IEEE DOI 2402
Tail, Training, Head, Feature extraction, Knowledge transfer, Representation learning, Noise measurement, knowledge transfer BibRef

Elbatel, M.[Marawan], Martí, R.[Robert], Li, X.M.[Xiao-Meng],
FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition,
MedImg(43), No. 3, March 2024, pp. 954-965.
IEEE DOI Code:
WWW Link. 2403
Biomedical imaging, Adaptation models, Task analysis, Tuning, Data models, Transformers, Image classification, Visual prompting, long tailed learning BibRef

Wang, W.Q.[Wei-Qiu], Chen, Z.[Zining], Su, F.[Fei], Zhao, Z.C.[Zhi-Cheng],
Text-guided Fourier Augmentation for long-tailed recognition,
PRL(179), 2024, pp. 38-44.
Elsevier DOI 2403
Long-tailed visual recognition, Language models, Fourier transform, Imbalanced data BibRef

Chen, J.H.[Jia-Hao], Su, B.[Bing],
Instance-Specific Semantic Augmentation for Long-Tailed Image Classification,
IP(33), 2024, pp. 2544-2557.
IEEE DOI 2404
Tail, Semantics, Head, Programmable logic arrays, Training, Image classification, Reliability, Long-tailed distribution, imbalanced data BibRef

Zhao, Q.H.[Qi-Hao], Zhang, F.[Fan], Hu, W.[Wei], Feng, S.[Songhe], Liu, J.[Jun],
OHD: An Online Category-Aware Framework for Learning With Noisy Labels Under Long-Tailed Distribution,
CirSysVideo(34), No. 5, May 2024, pp. 3806-3818.
IEEE DOI 2405
Noise measurement, Training, Tail, Frequency estimation, Uncertainty, Robustness, Deep neural networks, image classification BibRef

Ma, Y.B.[Yan-Biao], Jiao, L.C.[Li-Cheng], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan], Liu, X.[Xu], Chen, P.H.[Pu-Hua],
Geometric Prior Guided Feature Representation Learning for Long-Tailed Classification,
IJCV(132), No. 7, July 2024, pp. Pages2493-2510.
Springer DOI 2406
BibRef

Ma, Y.B.[Yan-Biao], Jiao, L.C.[Li-Cheng], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan], Liu, X.[Xu], Li, L.L.[Ling-Ling],
Curvature-Balanced Feature Manifold Learning for Long-Tailed Classification,
CVPR23(15824-15835)
IEEE DOI 2309
BibRef

Pan, H.L.[Hao-Lin], Guo, Y.[Yong], Yu, M.[Mianjie], Chen, J.[Jian],
Enhanced Long-Tailed Recognition With Contrastive CutMix Augmentation,
IP(33), 2024, pp. 4215-4230.
IEEE DOI Code:
WWW Link. 2408
BibRef

Xie, H.T.[Hong-Tao], Jiang, Y.[Yan], Zhang, L.[Lei], Li, P.D.[Pan-Deng], Zhang, D.M.[Dong-Ming], Zhang, Y.D.[Yong-Dong],
Semantic-Enhanced Proxy-Guided Hashing for Long-Tailed Image Retrieval,
MultMed(26), 2024, pp. 9499-9514.
IEEE DOI 2410
Semantics, Codes, Tail, Measurement, Training, Image retrieval, Covariance matrices, Deep hashing, long-tailed learning, similarity measuring BibRef

Zhang, E.[Enhao], Geng, C.X.[Chuan-Xing], Li, C.O.[Cha-Ohua], Chen, S.C.[Song-Can],
Dynamic Learnable Logit Adjustment for Long-Tailed Visual Recognition,
CirSysVideo(34), No. 9, September 2024, pp. 7986-7997.
IEEE DOI 2410
Tail, Training, Prototypes, Magnetic heads, Visualization, Standards, Vectors, Long-tailed learning, logit adjustment, algebraic rank, neural collapse BibRef

Zeng, W.[Wu], Xiao, Z.Y.[Zheng-Ying],
MinoritySalMix and adaptive semantic weight compensation for long-tailed classification,
IVC(152), 2024, pp. 105307.
Elsevier DOI 2412
Long-tailed classification, Data augmentation, Saliency detection, Adaptive sampling weights, Deep learning BibRef

Vu, D.Q.[Duc-Quang], Phung, T.T.T.[Trang T. T.], Wang, J.C.[Jia-Ching], Mai, S.T.[Son T.],
LCSL: Long-Tailed Classification via Self-Labeling,
CirSysVideo(34), No. 11, November 2024, pp. 12048-12058.
IEEE DOI Code:
WWW Link. 2412
Training, Accuracy, Predictive models, Data models, Data augmentation, Brain modeling, Training data, imbalance classification BibRef

Bao, Y.X.[Yu-Xiang], Kang, G.L.[Guo-Liang], Yang, L.L.[Lin-Lin], Duan, X.Y.[Xiao-Yue], Zhao, B.[Bo], Zhang, B.C.[Bao-Chang],
Normalizing Batch Normalization for Long-Tailed Recognition,
IP(34), 2025, pp. 209-220.
IEEE DOI 2501
Heavily-tailed distribution, Vectors, Batch normalization, Training, Standards, Accuracy, Visualization, Image recognition, deep learning BibRef

Guo, C.[Chen], Chen, W.L.[Wei-Ling], Huang, A.P.[Ai-Ping], Zhao, T.S.[Tie-Song],
Prototype Alignment With Dedicated Experts for Test-Agnostic Long-Tailed Recognition,
MultMed(27), 2025, pp. 455-465.
IEEE DOI 2501
Heavily-tailed distribution, Training, Prototypes, Tail, Pipelines, Semantics, Representation learning, Head, Visualization, prototypical learning BibRef

Zhang, E.[Enhao], Geng, C.X.[Chuan-Xing], Chen, S.C.[Song-Can],
Class-aware Universum Inspired re-balance learning for long-tailed recognition,
PR(161), 2025, pp. 111337.
Elsevier DOI 2502
Re-balance learning, Long-tailed recognition, Class-aware Universum, Higher-order mixup BibRef

Chang, X.H.[Xu-Hui], Zhai, J.H.[Jun-Hai], Qiu, S.X.[Shao-Xin], Sun, Z.R.[Zheng-Rong],
Rebalanced supervised contrastive learning with prototypes for long-tailed visual recognition,
CVIU(252), 2025, pp. 104291.
Elsevier DOI Code:
WWW Link. 2502
Long-tailed recognition, Imbalance learning, Supervised contrastive learning, Prototypes BibRef

Wei, X.S.[Xiu-Shen], Sun, X.H.[Xu-Hao], Shen, Y.[Yang], Wang, P.[Peng],
Delving Deep into Simplicity Bias for Long-Tailed Image Recognition,
IJCV(133), No. 6, June 2025, pp. Psges 3349-3366.
Springer DOI 2505
BibRef

Li, Z.[Zhuo], Zhao, H.[He], Gao, A.Z.[Anning-Zhe], Guo, D.D.[Dan-Dan], Chang, T.H.[Tsung-Hui], Wan, X.[Xiang],
Prototype-Oriented Clean Subset Extraction for Noisy Long-Tailed Classification,
CirSysVideo(35), No. 8, August 2025, pp. 7953-7965.
IEEE DOI Code:
WWW Link. 2508
Noise measurement, Noise, Heavily-tailed distribution, Training, Prototypes, Labeling, Reliability, Detectors, Data mining, Costs, optimal transport BibRef

Fan, S.N.[Sheng-Nan], Chai, Z.[Zhilei], Fang, Z.J.[Zhi-Jun], Pan, Y.Y.[Yu-Ying], Shen, H.[Hui], Cheng, X.Y.[Xiang-Yu], Wu, Q.[Qin],
MaxSwap-Enhanced Knowledge Consistency Learning for long-tailed recognition,
IVC(161), 2025, pp. 105643.
Elsevier DOI 2509
Long-tailed recognition, Data augmentation, Knowledge consistency learning, Multi-view learning, Confusion suppression BibRef

Zhao, W.[Wenyi], Li, W.[Wei], Li, Y.H.[Yu-Han], Yang, L.[Lu], Liang, Z.[Zhenhao], Hu, E.[Enwen], Zhang, W.D.[Wei-Dong], Yang, H.[Huihua],
Constructing Balanced Training Samples: A New Perspective on Long-Tailed Classification,
MultMed(27), 2025, pp. 5130-5143.
IEEE DOI 2509
Heavily-tailed distribution, Training, Feature extraction, Tail, Contrastive learning, Optimization, Measurement, Head, Data mining, end-to-end BibRef

Jin, L.[Lu], Lu, Z.Y.[Zheng-Yun], Li, Z.C.[Ze-Chao], Pan, Y.H.[Yong-Hua], Dai, L.Q.[Long-Quan], Tang, J.H.[Jin-Hui], Jain, R.[Ramesh],
Causal Inference Hashing for Long-Tailed Image Retrieval,
IP(34), 2025, pp. 5099-5114.
IEEE DOI Code:
WWW Link. 2509
Heavily-tailed distribution, Codes, Telecommunication traffic, Communication switching, Image retrieval, Head, Hash functions, causal inference BibRef

Deng, X.[Xiyan], Wang, X.L.[Xiao-Li], Sun, Y.F.[Yi-Fan], Zhao, X.S.[Xu-Sheng], Tian, S.[Siju], Li, M.Q.[Min-Qi], Wang, Y.P.[Yu-Ping],
EIFA-KD: Explicit and implicit feature augmentation with knowledge distillation for long-tailed visual data classification,
PR(171), 2026, pp. 112129.
Elsevier DOI 2510
Long-tailed visual data classification, Explicit feature augmentation, Implicit feature augmentation, Knowledge distillation BibRef

Ren, N.[Ning], Li, X.S.[Xiao-Song], Wu, Y.X.[Yan-Xia], Fu, Y.[Yan],
Bi-granularity balance learning for long-tailed image classification,
CVIU(261), 2025, pp. 104469.
Elsevier DOI 2511
Convolutional neural networks, Long-tailed image classification, Imbalanced learning, Contrastive learning BibRef

Huang, Z.Y.[Zhen-Yuan], Tang, W.Z.[Wen-Zhong], Zhang, H.[Hui], Yang, H.J.[Hai-Jun],
A general aggregation federated learning intervention algorithm based on do-calculus,
PR(171), 2026, pp. 112210.
Elsevier DOI 2511
Long-tail learning, Heterogeneous data, Causal intervention BibRef


Sidhu, M.[Mankeerat], Chopra, H.[Hetarth], Blume, A.[Ansel], Kim, J.[Jeonghwan], Reddy, R.G.[Revanth Gangi], Ji, H.[Heng],
Search and Detect: Training-Free Long Tail Object Detection via Web-Image Retrieval,
CVPR25(15129-15138)
IEEE DOI 2508
Training, Heavily-tailed distribution, Annotations, Computational modeling, Object detection, Detectors, fine grained image classification BibRef

Jung, Y.G.[Yoon Gyo], Park, J.[Jaewoo], Yoon, J.[Jaeho], Peng, K.C.[Kuan-Chuan], Kim, W.[Wonchul], Teoh, A.B.J.[Andrew Beng Jin], Camps, O.[Octavia],
TailedCore: Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly Detection,
CVPR25(25539-25548)
IEEE DOI 2508
Heavily-tailed distribution, Navigation, Noise, Telecommunication traffic, Predictive models, Noise robustness, noisy long-tail anomaly detection BibRef

Zhao, S.Z.[Shi-Zhen], Wen, X.[Xin], Liu, J.H.[Jia-Hui], Ma, C.F.[Chuo-Fan], Yuan, C.F.[Chun-Feng], Qi, X.J.[Xiao-Juan],
Learning from Neighbors: Category Extrapolation for Long-Tail Learning,
CVPR25(30483-30492)
IEEE DOI 2508
Training, Representation learning, Deep learning, Extrapolation, Heavily-tailed distribution, Head, Large language models, Standards BibRef

Li, Z.[Ziang], Zhang, H.G.[Hong-Guang], Wang, J.[Juan], Chen, M.H.[Mei-Hui], Hu, H.X.[Hong-Xin], Yi, W.Z.[Wen-Zhe], Xu, X.Y.[Xiao-Yang], Yang, M.[Mengda], Ma, C.J.[Chen-Jun],
From Head to Tail: Efficient Black-box Model Inversion Attack via Long-tailed Learning,
CVPR25(29288-29298)
IEEE DOI Code:
WWW Link. 2508
Training, Heavily-tailed distribution, Head, Closed box, Training data, Data models, Robustness, Optimization, Residual neural networks BibRef

Yu-Hang, W.[Wang], Guo, J.[Junkang], Liu, A.[Aolei], Wang, K.[Kaihao], Wu, Z.[Zaitong], Liu, Z.Y.[Zhen-Yu], Yin, W.F.[Wen-Fei], Liu, J.[Jian],
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions,
CVPR25(15476-15485)
IEEE DOI Code:
WWW Link. 2508
Training, Measurement, Heavily-tailed distribution, Accuracy, Memory management, Robustness, Computational efficiency, real-world robustness BibRef

Bhat, S.D.[S. Divakar], More, A.[Amit], Soni, M.[Mudit], Agrawal, S.[Surbhi],
Prior2Posterior: Model Prior Correction for Long-Tailed Learning,
WACV25(1289-1298)
IEEE DOI 2505
Training, Analytical models, Heavily-tailed distribution, Face recognition, Tail, Probability, Predictive models, recognition BibRef

Jung, H.[Hoin], Wang, X.Q.[Xiao-Qian],
Towards On-the-Fly Novel Category Discovery in Dynamic Long-Tailed Distributions,
WACV25(6795-6804)
IEEE DOI 2505
Training, Heavily-tailed distribution, Accuracy, Sparse approximation, Navigation, Heuristic algorithms, Merging, online learning BibRef

Yu, T.[Tao], Zhao, X.[Xu], An, Y.Q.[Yong-Qi], Tang, M.[Ming], Wang, J.Q.[Jin-Qiao],
Knowledge Distillation Dealing with Sample-wise Long-tail Problem,
ACCV24(X: 411-427).
Springer DOI 2412
BibRef

Lin, D.K.[De-Kun], Peng, T.[Tailai], Chen, R.[Rui], Xie, X.R.[Xin-Ran], Qin, X.L.[Xiao-Lin], Cui, Z.[Zhe],
Distributionally Robust Loss for Long-tailed Multi-label Image Classification,
ECCV24(XXXIII: 417-433).
Springer DOI 2412
BibRef

Aimar, E.S.[Emanuel Sanchez], Helgesen, N.[Nathaniel], Xu, Y.H.[Yong-Hao], Kuhlmann, M.[Marco], Felsberg, M.[Michael],
Flexible Distribution Alignment: Towards Long-tailed Semi-supervised Learning with Proper Calibration,
ECCV24(LIV: 307-327).
Springer DOI 2412
BibRef

Zhao, Q.H.[Qi-Hao], Dai, Y.[Yalun], Lin, S.[Shen], Hu, W.[Wei], Zhang, F.[Fan], Liu, J.[Jun],
LTRL: Boosting Long-tail Recognition via Reflective Learning,
ECCV24(LXVII: 1-18).
Springer DOI 2412
BibRef

Zheng, H.W.[Hong-Wei], Zhou, L.Y.[Lin-Yuan], Li, H.[Han], Su, J.M.[Jin-Ming], Wei, X.M.[Xiao-Ming], Xu, X.M.[Xiao-Ming],
BEM: Balanced and Entropy-Based Mix for Long-Tailed Semi-Supervised Learning,
CVPR24(22893-22903)
IEEE DOI 2410
Training, Uncertainty, Accuracy, Semisupervised learning, Benchmark testing, Semi-supervised learning, Data augmentation BibRef

Yue, X.[Xinli], Mou, N.P.[Ning-Ping], Wang, Q.[Qian], Zhao, L.C.[Ling-Chen],
Revisiting Adversarial Training Under Long-Tailed Distributions,
CVPR24(24492-24501)
IEEE DOI Code:
WWW Link. 2410
Training, Codes, Computational modeling, Training data, Data augmentation BibRef

Khorram, S.[Saeed], Jiang, M.Q.[Ming-Qi], Shahbazi, M.[Mohamad], Danesh, M.H.[Mohamad H.], Fuxin, L.[Li],
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions,
CVPR24(7580-7590)
IEEE DOI Code:
WWW Link. 2410
Training, Measurement, Image resolution, Head, Image synthesis, Training data, Tail, long-tail, GAN, long-tail generative learning, class imbalance BibRef

Gu, Y.[Yanan], Yang, M.[Muli], Yang, X.[Xu], Wei, K.[Kun], Zhu, H.Y.[Hong-Yuan], Goenawan, G.J.[Gabriel James], Deng, C.[Cheng],
Dynamic Adapter Tuning for Long-Tailed Class-Incremental Learning,
WACV25(8176-8185)
IEEE DOI 2505
Training, Adaptation models, Visualization, Heavily-tailed distribution, Foundation models, Tail, Faces BibRef

Wang, X.[Xi], Yang, X.[Xu], Yin, J.[Jie], Wei, K.[Kun], Deng, C.[Cheng],
Long-Tail Class Incremental Learning via Independent SUb-Prototype Construction,
CVPR24(28598-28607)
IEEE DOI 2410
Incremental learning, Extraterrestrial phenomena, Computational modeling, Collaboration, Benchmark testing, Vectors BibRef

Han, P.X.[Peng-Xiao], Ye, C.K.[Chang-Kun], Zhou, J.[Jieming], Zhang, J.[Jing], Hong, J.[Jie], Li, X.S.[Xue-Song],
Latent-based Diffusion Model for Long-tailed Recognition,
L3D-IVU24(2639-2648)
IEEE DOI 2410
Training, Computational modeling, Transfer learning, Noise reduction, Tail, diffusion model, long-tailed recognition, imbalance distribution BibRef

Lavoie, M.A.[Marc-Antoine], Waslander, S.L.[Steven L.],
Class Instance Balanced Learning for Long-Tailed Classification,
CRV23(121-128)
IEEE DOI 2406
Training, Head, Training data, Tail, Artificial neural networks, Task analysis, Robots, classification, contrastive learning, long tailed classification BibRef

Kalla, J.[Jayateja], Biswas, S.[Soma],
Robust Feature Learning and Global Variance-Driven Classifier Alignment for Long-Tail Class Incremental Learning,
WACV24(32-41)
IEEE DOI Code:
WWW Link. 2404
Representation learning, Power measurement, Codes, Prototypes, Tail, Data models, Algorithms, Machine learning architectures, Image recognition and understanding BibRef

Zhang, S.[Shan], Ni, Y.[Yao], Du, J.H.[Jin-Hao], Liu, Y.X.[Yan-Xia], Koniusz, P.[Piotr],
Semantic Transfer from Head to Tail: Enlarging Tail Margin for Long-Tailed Visual Recognition,
WACV24(1339-1349)
IEEE DOI 2404
Training, Visualization, Head, Semantics, Tail, Benchmark testing, Fasteners, Algorithms, Image recognition and understanding, Virtual / augmented reality BibRef

Li, L.J.[Lin-Jie], Wu, Z.Y.[Zhen-Yu], Liu, J.M.[Jia-Ming], Ji, Y.[Yang],
TAE: Task-aware Expandable Representation for Long Tail Class Incremental Learning,
ACCV24(IV: 335-351).
Springer DOI 2412
BibRef

Lu, Y.[Yang], Zhang, Y.L.[Yi-Liang], Han, B.[Bo], Cheung, Y.M.[Yiu-Ming], Wang, H.Z.[Han-Zi],
Label-Noise Learning with Intrinsically Long-Tailed Data,
ICCV23(1369-1378)
IEEE DOI Code:
WWW Link. 2401
BibRef

Tao, Y.F.[Ying-Fan], Sun, J.[Jingna], Yang, H.[Hao], Chen, L.[Li], Wang, X.[Xu], Yang, W.M.[Wen-Ming], Du, D.[Daniel], Zheng, M.[Min],
Local and Global Logit Adjustments for Long-Tailed Learning,
ICCV23(11749-11758)
IEEE DOI 2401
BibRef

Chen, X.H.[Xiao-Hua], Zhou, Y.[Yucan], Wu, D.[Dayan], Yang, C.[Chule], Li, B.[Bo], Hu, Q.H.[Qing-Hua], Wang, W.P.[Wei-Ping],
AREA: Adaptive Reweighting via Effective Area for Long-Tailed Classification,
ICCV23(19220-19230)
IEEE DOI Code:
WWW Link. 2401
BibRef

Park, M.H.[Min-Ho], Kim, H.I.[Hyung-Il], Song, H.J.[Hwa Jeon], Kang, D.O.[Dong-Oh],
Augmenting Features via Contrastive Learning-based Generative Model for Long-Tailed Classification,
LIMIT23(1010-1019)
IEEE DOI 2401
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Zhao, Q.H.[Qi-Hao], Jiang, C.[Chen], Hu, W.[Wei], Zhang, F.[Fan], Liu, J.[Jun],
MDCS: More Diverse Experts with Consistency Self-distillation for Long-tailed Recognition,
ICCV23(11563-11574)
IEEE DOI Code:
WWW Link. 2401
BibRef

Lin, C.S.[Ci-Siang], Chen, M.H.[Min-Hung], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Frequency-Aware Self-Supervised Long-Tailed Learning,
LIMIT23(963-972)
IEEE DOI 2401
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Park, W.[Wongi], Park, I.[Inhyuk], Kim, S.[Sungeun], Ryu, J.B.[Jong-Bin],
Robust Asymmetric Loss for Multi-Label Long-Tailed Learning,
CVAMD23(2703-2712)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yamagishi, Y.[Yosuke], Hanaoka, S.[Shohei],
Effect of Stage Training for Long-Tailed Multi-Label Image Classification,
CVAMD23(2713-2720)
IEEE DOI 2401
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Zhang, W.Q.[Wen-Qiao], Liu, C.S.[Chang-Shuo], Zeng, L.Z.[Ling-Ze], Ooi, B.C.[Beng-Chin], Tang, S.L.[Si-Liang], Zhuang, Y.T.[Yue-Ting],
Learning in Imperfect Environment: Multi-Label Classification with Long-Tailed Distribution and Partial Labels,
ICCV23(1423-1432)
IEEE DOI Code:
WWW Link. 2401
BibRef

Nah, W.J.[Wan Jun], Ng, C.C.[Chun Chet], Lin, C.T.[Che-Tsung], Lee, Y.K.[Yeong Khang], Kew, J.L.[Jie Long], Tan, Z.Q.[Zhi Qin], Chan, C.S.[Chee Seng], Zach, C.[Christopher], Lai, S.H.[Shang-Hong],
Rethinking Long-Tailed Visual Recognition with Dynamic Probability Smoothing and Frequency Weighted Focusing,
ICIP23(435-439)
IEEE DOI Code:
WWW Link. 2312
BibRef

Perrett, T.[Toby], Sinha, S.[Saptarshi], Burghardt, T.[Tilo], Mirmehdi, M.[Majid], Damen, D.[Dima],
Use Your Head: Improving Long-Tail Video Recognition,
CVPR23(2415-2425)
IEEE DOI 2309
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Wei, T.[Tong], Gan, K.[Kai],
Towards Realistic Long-Tailed Semi-Supervised Learning: Consistency is All You Need,
CVPR23(3469-3478)
IEEE DOI 2309
BibRef

Gou, Y.B.[Yuan-Biao], Hu, P.[Peng], Lv, J.C.[Jian-Cheng], Zhu, H.Y.[Hong-Yuan], Peng, X.[Xi],
Rethinking Image Super Resolution from Long-Tailed Distribution Learning Perspective,
CVPR23(14327-14336)
IEEE DOI 2309
BibRef

Du, Y.X.[Ying-Xiao], Wu, J.X.[Jian-Xin],
No One Left Behind: Improving the Worst Categories in Long-Tailed Learning,
CVPR23(15804-15813)
IEEE DOI 2309
BibRef

Du, F.[Fei], Yang, P.[Peng], Jia, Q.[Qi], Nan, F.T.[Feng-Tao], Chen, X.T.[Xiao-Ting], Yang, Y.[Yun],
Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions,
CVPR23(15814-15823)
IEEE DOI 2309
BibRef

Aimar, E.S.[Emanuel Sanchez], Jonnarth, A.[Arvi], Felsberg, M.[Michael], Kuhlmann, M.[Marco],
Balanced Product of Calibrated Experts for Long-Tailed Recognition,
CVPR23(19967-19977)
IEEE DOI 2309
BibRef

Jin, Y.[Yan], Li, M.K.[Meng-Ke], Lu, Y.[Yang], Cheung, Y.M.[Yiu-Ming], Wang, H.Z.[Han-Zi],
Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation,
CVPR23(23695-23704)
IEEE DOI 2309
BibRef

Li, J.[Jian], Meng, Z.[Ziyao], Shi, D.[Daqian], Song, R.[Rui], Diao, X.L.[Xiao-Lei], Wang, J.W.[Jing-Wen], Xu, H.[Hao],
FCC: Feature Clusters Compression for Long-Tailed Visual Recognition,
CVPR23(24080-24089)
IEEE DOI 2309
BibRef

Cai, F.[Feng], Wu, K.Y.[Ke-Yu], Wang, H.P.[Hai-Peng], Wang, F.[Feng],
A Three-Stage Framework with Reliable Sample Pool for Long-Tailed Classification,
PBVS23(479-486)
IEEE DOI 2309
BibRef

Long, H.X.[Hai-Xu], Zhang, X.L.[Xiao-Lin], Liu, Y.B.[Yan-Bin], Luo, Z.T.[Zong-Tai], Liu, J.B.[Jian-Bo],
Mutual Exclusive Modulator for Long-Tailed Recognition,
L3D-IVU23(4891-4900)
IEEE DOI 2309
BibRef

Chen, J.H.[Jia-Hao], Su, B.[Bing],
Transfer Knowledge from Head to Tail: Uncertainty Calibration under Long-tailed Distribution,
CVPR23(19978-19987)
IEEE DOI 2309
BibRef

Zhou, Z.P.[Zhi-Peng], Li, L.Q.[Lan-Qing], Zhao, P.L.[Pei-Lin], Heng, P.A.[Pheng-Ann], Gong, W.[Wei],
Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition,
CVPR23(3499-3509)
IEEE DOI 2309
BibRef

Fu, S.[Siming], Chu, H.P.[Huan-Peng], He, X.X.[Xiao-Xuan], Wang, H.L.[Hua-Liang], Yang, Z.Y.[Zhen-Yu], Hu, H.J.[Hao-Ji],
Meta-prototype Decoupled Training for Long-tailed Learning,
ACCV22(VI:252-268).
Springer DOI 2307
BibRef

Peng, H.Y.[Han-Yu], Pian, W.G.[Wei-Guo], Sun, M.M.[Ming-Ming], Li, P.[Ping],
Dynamic Re-weighting for Long-tailed Semi-supervised Learning,
WACV23(6453-6463)
IEEE DOI 2302
Training, Uncertainty, Annotations, Semisupervised learning, Task analysis, Algorithms: Machine learning architectures, visual reasoning BibRef

Park, C.[Changhwa], Yim, J.[Junho], Jun, E.[Eunji],
Mutual Learning for Long-Tailed Recognition,
WACV23(2674-2683)
IEEE DOI 2302
Training, Deep learning, Image recognition, Neural networks, Tail, Benchmark testing, Algorithms: Machine learning architectures, visual reasoning BibRef

Liu, B.[Bo], Li, H.X.[Hao-Xiang], Kang, H.[Hao], Hua, G.[Gang], Vasconcelos, N.M.[Nuno M.],
Breadcrumbs: Adversarial Class-Balanced Sampling for Long-Tailed Recognition,
ECCV22(XXIV:637-653).
Springer DOI 2211
BibRef

Tang, K.H.[Kai-Hua], Tao, M.Y.[Ming-Yuan], Qi, J.X.[Jia-Xin], Liu, Z.G.[Zhen-Guang], Zhang, H.W.[Han-Wang],
Invariant Feature Learning for Generalized Long-Tailed Classification,
ECCV22(XXIV:709-726).
Springer DOI 2211
BibRef

Hong, Y.[Yan], Zhang, J.[Jianfu], Sun, Z.Y.[Zhong-Yi], Yan, K.[Ke],
SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification,
ECCV22(XXIV:587-603).
Springer DOI 2211
BibRef

Wang, H.L.[Hua-Liang], Fu, S.M.[Si-Ming], He, X.X.[Xiao-Xuan], Fang, H.X.[Hang-Xiang], Liu, Z.Z.[Zuo-Zhu], Hu, H.J.[Hao-Ji],
Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-Tailed Learning,
ECCV22(XXIV:179-196).
Springer DOI 2211
BibRef

Cho, J.H.[Jang Hyun], Krähenbühl, P.[Philipp],
Long-tail Detection with Effective Class-Margins,
ECCV22(VIII:698-714).
Springer DOI 2211
BibRef

Rangwani, H.[Harsh], Jaswani, N.[Naman], Karmali, T.[Tejan], Jampani, V.[Varun], Babu, R.V.[R. Venkatesh],
Improving GANs for Long-Tailed Data Through Group Spectral Regularization,
ECCV22(XV:426-442).
Springer DOI 2211
BibRef

Jiang, C.M.[Chiyu Max], Najibi, M.[Mahyar], Qi, C.R.[Charles R.], Zhou, Y.[Yin], Anguelov, D.[Dragomir],
Improving the Intra-class Long-Tail in 3D Detection via Rare Example Mining,
ECCV22(X:158-175).
Springer DOI 2211
BibRef

Yang, Y.Z.[Yu-Zhe], Wang, H.[Hao], Katabi, D.[Dina],
On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond,
ECCV22(XX:57-75).
Springer DOI 2211
BibRef

Gu, X.[Xiao], Guo, Y.[Yao], Li, Z.[Zeju], Qiu, J.N.[Jia-Ning], Dou, Q.[Qi], Liu, Y.X.[Yu-Xuan], Lo, B.[Benny], Yang, G.Z.[Guang-Zhong],
Tackling Long-Tailed Category Distribution Under Domain Shifts,
ECCV22(XXIII:727-743).
Springer DOI 2211
BibRef

Tian, C.Y.[Chang-Yao], Wang, W.H.[Wen-Hai], Zhu, X.Z.[Xi-Zhou], Dai, J.F.[Ji-Feng], Qiao, Y.[Yu],
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition,
ECCV22(XXV:73-91).
Springer DOI 2211
BibRef

Yi, X.Y.[Xuan-Yu], Tang, K.[Kaihua], Hua, X.S.[Xian-Sheng], Lim, J.H.[Joo-Hwee], Zhang, H.W.[Han-Wang],
Identifying Hard Noise in Long-Tailed Sample Distribution,
ECCV22(XXVI:739-756).
Springer DOI 2211
BibRef

Alshammari, S.[Shaden], Wang, Y.X.[Yu-Xiong], Ramanan, D.[Deva], Kong, S.[Shu],
Long-Tailed Recognition via Weight Balancing,
CVPR22(6887-6897)
IEEE DOI 2210
Training, Art, Benchmark testing, Data models, Tuning, Transfer/low-shot/long-tail learning BibRef

Li, M.K.[Meng-Ke], Cheung, Y.M.[Yiu-Ming], Lu, Y.[Yang],
Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment,
CVPR22(6919-6928)
IEEE DOI 2210
Training, Visualization, Graphical models, Perturbation methods, Neural networks, Tail, Benchmark testing, Transfer/low-shot/long-tail learning BibRef

Parisot, S.[Sarah], Esperança, P.M.[Pedro M.], McDonagh, S.[Steven], Madarasz, T.J.[Tamas J.], Yang, Y.X.[Yong-Xin], Li, Z.G.[Zhen-Guo],
Long-tail Recognition via Compositional Knowledge Transfer,
CVPR22(6929-6938)
IEEE DOI 2210
Training, Analytical models, Prototypes, Tail, Performance gain, Benchmark testing, Transfer/low-shot/long-tail learning BibRef

Long, A.[Alexander], Yin, W.[Wei], Ajanthan, T.[Thalaiyasingam], Nguyen, V.[Vu], Purkait, P.[Pulak], Garg, R.[Ravi], Blair, A.[Alan], Shen, C.H.[Chun-Hua], van den Hengel, A.J.[Anton J.],
Retrieval Augmented Classification for Long-Tail Visual Recognition,
CVPR22(6949-6959)
IEEE DOI 2210
Training, Visualization, Pipelines, Memory management, Tail, Transfer/low-shot/long-tail learning, retrieval BibRef

Li, B.[Bolian], Han, Z.[Zongbo], Li, H.[Haining], Fu, H.Z.[Hua-Zhu], Zhang, C.Q.[Chang-Qing],
Trustworthy Long-Tailed Classification,
CVPR22(6960-6969)
IEEE DOI 2210
Measurement, Ethics, Evidence theory, Estimation, Distributed databases, Tail, Machine learning, privacy and ethics in vision BibRef

Oh, Y.[Youngtaek], Kim, D.J.[Dong-Jin], Kweon, I.S.[In So],
DASO: Distribution-Aware Semantics-Oriented Pseudo-label for Imbalanced Semi-Supervised Learning,
CVPR22(9776-9786)
IEEE DOI 2210
Semantics, Prototypes, Semisupervised learning, Benchmark testing, Reliability, Transfer/low-shot/long-tail learning BibRef

Sharma, S.[Saurabh], Yu, N.[Ning], Fritz, M.[Mario], Schiele, B.[Bernt],
Long-Tailed Recognition Using Class-Balanced Experts,
GCPR20(86-100).
Springer DOI 2110
BibRef

Zhou, B., Cui, Q., Wei, X., Chen, Z.,
BBN: Bilateral-Branch Network With Cumulative Learning for Long-Tailed Visual Recognition,
CVPR20(9716-9725)
IEEE DOI 2008
Training, Error analysis, Feature extraction, Data models, Visualization, Benchmark testing BibRef

Zhu, L.C.[Lin-Chao], Yang, Y.[Yi],
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition,
CVPR20(4343-4352)
IEEE DOI 2008
Visualization, Prototypes, Training, Feature extraction, Robustness, Data models, Encoding BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Unbalanced Data, Oversample or Undersample Solutions .


Last update:Nov 10, 2025 at 14:27:42