Toward Fast, Flexible, and Robust Low-Light Image Enhancement

@article{Ma2022TowardFF,
  title={Toward Fast, Flexible, and Robust Low-Light Image Enhancement},
  author={Long Ma and Tengyu Ma and Risheng Liu and Xin Fan and Zhongxuan Luo},
  journal={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2022},
  pages={5627-5636}
}
  • Long MaTengyu Ma Zhongxuan Luo
  • Published 21 April 2022
  • Physics
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Existing low-light image enhancement techniques are mostly not only difficult to deal with both visual quality and computational efficiency but also commonly invalid in unknown complex scenarios. In this paper, we develop a new Self-Calibrated Illumination (SCI) learning framework for fast, flexible, and robust brightening images in real-world low-light scenarios. To be specific, we establish a cascaded illumination learning process with weight sharing to handle this task. Considering the… 
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