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Elsevier DOI
1804
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Springer DOI
1506
Boosting, Multi-class classification,
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PR(130), 2022, pp. 108781.
Elsevier DOI
2206
Object detection, Class imbalance, Residual objectness
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IET-CV(17), No. 5, 2023, pp. 565-575.
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2309
learning (artificial intelligence), object detection
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Tan, J.R.[Jing-Ru],
Li, B.[Bo],
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Yao, Y.Q.[Yong-Qiang],
Yu, F.W.[Feng-Wei],
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The Equalization Losses: Gradient-Driven Training for Long-tailed
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IEEE DOI
2310
BibRef
Yang, J.X.[Jia-Xin],
Yu, M.M.[Miao-Miao],
Li, S.[Shuohao],
Zhang, J.[Jun],
Hu, S.Z.[Sheng-Ze],
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DOI Link
2310
BibRef
Shao, M.W.[Ming-Wen],
Peng, Z.[Zilu],
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IVC(142), 2024, pp. 104888.
Elsevier DOI
2402
Deep convolutional neural network, Object detection,
Long-tail distribution, Metric learning, Feature extraction
BibRef
Qi, T.H.[Tian-Hao],
Xie, H.T.[Hong-Tao],
Li, P.[Pandeng],
Ge, J.N.[Jian-Nan],
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Balanced Classification:
A Unified Framework for Long-Tailed Object Detection,
MultMed(26), 2024, pp. 3088-3101.
IEEE DOI
2402
Tail, Detectors, Training, Object detection, Feature extraction, Head,
Task analysis, Long-tailed object detection, Feature hallucination module
BibRef
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Teng, Y.[Yao],
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IJCV(132), No. 6, June 2024, pp. 2114-2134.
Springer DOI
2406
BibRef
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Liu, H.S.[Hai-Song],
Guo, S.[Sheng],
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StageInteractor: Query-based Object Detector with Cross-stage
Interaction,
ICCV23(6554-6565)
IEEE DOI Code:
WWW Link.
2401
BibRef
Pan, C.[Cong],
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Distribution, and Multi-Labels,
PAMI(46), No. 12, December 2024, pp. 9255-9271.
IEEE DOI
2411
Object detection, Annotations, Training, Detectors, Deep learning,
Toy manufacturing industry, Automobiles, object detection,
multi-labels
BibRef
Peng, J.[Junran],
Bu, X.Y.[Xing-Yuan],
Sun, M.,
Zhang, Z.X.[Zhao-Xiang],
Tan, T.,
Yan, J.,
Large-Scale Object Detection in the Wild From Imbalanced Multi-Labels,
CVPR20(9706-9715)
IEEE DOI
2008
Object detection, Training, Machine learning, Automobiles,
Toy manufacturing industry, Sampling methods, Detectors
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Dong, N.[Na],
Zhang, Y.Q.[Yong-Qiang],
Ding, M.L.[Ming-Li],
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Boosting Long-tailed Object Detection via Step-wise Learning on
Smooth-tail Data,
ICCV23(6917-6926)
IEEE DOI Code:
WWW Link.
2401
BibRef
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Reconciling Object-Level and Global-Level Objectives for Long-Tail
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ICCV23(18936-18946)
IEEE DOI Code:
WWW Link.
2401
BibRef
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Cao, J.[Jian],
Fu, T.H.[Tian-Hao],
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Boosting Dense Long-tailed Object Detection from Data-centric View,
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Springer DOI
2307
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Zhu, Y.[Yousong],
Chen, Y.Y.[Ying-Ying],
Zhao, C.Y.[Chao-Yang],
Yu, B.[Bin],
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Tang, M.[Ming],
C2AM Loss: Chasing a Better Decision Boundary for Long-Tail Object
Detection,
CVPR22(6970-6979)
IEEE DOI
2210
Adaptation models, Sensitivity, Object detection, Detectors, Tail,
Transfer/low-shot/long-tail learning,
retrieval
BibRef
Choi, J.W.[Jong-Won],
Yi, K.M.[Kwang Moo],
Kim, J.[Jihoon],
Choo, J.H.[Jin-Ho],
Kim, B.J.[Byoung-Jip],
Chang, J.[Jinyeop],
Gwon, Y.J.[Young-June],
Chang, H.J.[Hyung Jin],
VaB-AL: Incorporating Class Imbalance and Difficulty with Variational
Bayes for Active Learning,
CVPR21(6745-6754)
IEEE DOI
2111
Training, Learning systems, Estimation,
Object detection, Task analysis
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Yu, W.P.[Wei-Ping],
Yang, T.[Taojiannan],
Chen, C.[Chen],
Towards Resolving the Challenge of Long-tail Distribution in UAV
Images for Object Detection,
WACV21(3257-3266)
IEEE DOI
2106
Head, Image resolution, Computational modeling, Object detection, Detectors
BibRef
Wang, T.[Tong],
Zhu, Y.S.[You-Song],
Zhao, C.Y.[Chao-Yang],
Zeng, W.[Wei],
Wang, J.Q.[Jin-Qiao],
Tang, M.[Ming],
Adaptive Class Suppression Loss for Long-Tail Object Detection,
CVPR21(3102-3111)
IEEE DOI
2111
Training, Adaptation models, Vocabulary, Head, Object detection, Manuals
BibRef
Zhang, S.Y.[Song-Yang],
Li, Z.[Zeming],
Yan, S.P.[Shi-Peng],
He, X.M.[Xu-Ming],
Sun, J.[Jian],
Distribution Alignment:
A Unified Framework for Long-tail Visual Recognition,
CVPR21(2361-2370)
IEEE DOI
2111
Deep learning, Visualization, Image segmentation,
Semantics, Object detection
BibRef
Zhang, C.[Cheng],
Pan, T.Y.[Tai-Yu],
Li, Y.D.[Yan-Dong],
Hu, H.X.[He-Xiang],
Xuan, D.[Dong],
Changpinyo, S.[Soravit],
Gong, B.Q.[Bo-Qing],
Chao, W.L.[Wei-Lun],
MosaicOS: A Simple and Effective Use of Object-Centric Images for
Long-Tailed Object Detection,
ICCV21(407-417)
IEEE DOI
2203
Training, Image segmentation, Computational modeling,
Object detection, Detectors, Recognition and classification,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Li, Y.,
Wang, T.,
Kang, B.,
Tang, S.,
Wang, C.,
Li, J.,
Feng, J.,
Overcoming Classifier Imbalance for Long-Tail Object Detection With
Balanced Group Softmax,
CVPR20(10988-10997)
IEEE DOI
2008
Training, Object detection, Proposals, Adaptation models,
Feature extraction, Computational modeling, Detectors
BibRef
Tan, J.,
Wang, C.,
Li, B.,
Li, Q.,
Ouyang, W.,
Yin, C.,
Yan, J.,
Equalization Loss for Long-Tailed Object Recognition,
CVPR20(11659-11668)
IEEE DOI
2008
Training, Task analysis, Proposals, Detectors, Object recognition,
Object detection
BibRef
Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Dense Object Detection .