长尾分布（ImageClassification）
long-tailed distribution
重采样（re-sampling）
1. Decoupling reprentation and classifier for long-tailed recognition.(Image) (ICLR 2020)
2. BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition (Image)（CVPR20 oral）
3. Dynamic Curriculum Learning for Imbalanced Data Classification.(Face) (ICCV 2019)
重加权（re-weighting）
1. Class-Balanced Loss Bad on Effective Number of Samples. (Image) (CVPR 2019)
2. Learning Imbalanced Datats with Label-Distribution-Aware Margin Loss. (Image) (NIPS 2019)
3. Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective.(Image)
(CVPR 2020)
4. Remix: Rebalanced Mixup, (Arxiv Preprint 2020)
迁移学习（transfer learning）相关
1. Deep Reprentation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective.(CVPR 2020)
2. Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification.(ECCV 2020)
3. Large-Scale Long-Tailed Recognition in an Open World. (CVPR 2019)
顶会paper：
1. Rethinking the Value of Labels for Improving Class-Imbalanced Learning， Arxiv Preprint 2020
2. Learning to Segment the Tail, CVPR 2020
3.
4. Equalization Loss for Long-Tailed Object Recognition, CVPR 2020
5. Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax, CVPR 2020
6.
7. Domain Balancing: Face Recognition on Long-Tailed Domains (CVPR20)
8. Decoupling reprentation and classifier for long-tailed recognition.(ICLR 2020)
9. Feature Space Augmentation for Long-Tailed Data (Image) (ECCV2020)
10.Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datats（Multi-Label ) ( ECCV 2020 ）
0. ELF: An Early-Exiting Framework for Long-Tailed Classification， Arxiv Preprint 2020
往年：
10. Focal Loss for Den Object Detection, ICCV 2017
