@inproceedings{fdc3449271b1486eb7061c5f4c3eb7a6,
title = "Increasing Oversampling Diversity for Long-Tailed Visual Recognition",
abstract = "The long-tailed data distribution in real-world greatly increases the difficulty of training deep neural networks. Oversampling minority classes is one of the commonly used techniques to tackle this problem. In this paper, we first analyze that the commonly used oversampling technique tends to distort the representation learning and harm the network{\textquoteright}s generalizability. Then we propose two novel methods to increase the minority feature{\textquoteright}s diversity to alleviate such issue. Specifically, from the data perspective, we propose a mixup-based Synthetic Minority Over-sampling TEchnique called mixSMOTE, where tail class samples are synthesized from head classes so that a balanced training distribution can be obtained. Then from the model perspective, we propose Gradient Re-weighting Module (GRM) to re-distribute each instance{\textquoteright}s gradient contribution to the representation learning network. Extensive experiments on the long-tailed benchmark CIFAR10-LT, CIFAR100-LT and ImageNet-LT demonstrate the effectiveness of our proposed method.",
keywords = "Data imbalance, Long-tailed classification, Oversampling",
author = "Liuyu Xiang and Guiguang Ding and Jungong Han",
note = "Funding Information: Acknowledgement. This work was supported by the National Natural Science Foundation of China (No. U1936202, 61925107). Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 1st CAAI International Conference on Artificial Intelligence, CICAI 2021 ; Conference date: 05-06-2021 Through 06-06-2021",
year = "2022",
month = jan,
day = "1",
doi = "10.1007/978-3-030-93046-2_4",
language = "English",
isbn = "9783030930455",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "39--50",
editor = "Lu Fang and Yiran Chen and Guangtao Zhai and Jane Wang and Ruiping Wang and Weisheng Dong",
booktitle = "Artificial Intelligence - 1st CAAI International Conference, CICAI 2021, Proceedings",
address = "Switzerland",
}