Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

@article{Zhang2021DistributionAA,
  title={Distribution Alignment: A Unified Framework for Long-tail Visual Recognition},
  author={Songyang Zhang and Zeming Li and Shipeng Yan and Xuming He and Jian Sun},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={2361-2370}
}
  • Songyang ZhangZeming Li Jian Sun
  • Published 30 March 2021
  • Computer Science
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Despite the recent success of deep neural networks, it remains challenging to effectively model the long-tail class distribution in visual recognition tasks. To address this problem, we first investigate the performance bottleneck of the two-stage learning framework via ablative study. Motivated by our discovery, we propose a unified distribution alignment strategy for long-tail visual recognition. Specifically, we develop an adaptive calibration function that enables us to adjust the… 

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