Corpus ID: 199405526

Attention-guided Low-light Image Enhancement

@article{Lv2019AttentionguidedLI,
  title={Attention-guided Low-light Image Enhancement},
  author={Feifan Lv and F. Lu},
  journal={ArXiv},
  year={2019},
  volume={abs/1908.00682}
}
  • Feifan Lv, F. Lu
  • Published 2019
  • Computer Science, Engineering
  • ArXiv
  • Low-light image enhancement is a challenging task since various factors, including brightness, contrast, artifacts and noise, should be handled simultaneously and effectively. [...] Key Method In particular, the first attention map distinguishes underexposed regions from normally exposed regions, while the second attention map distinguishes noises from real-world textures. Under their guidance, the proposed multi-branch enhancement network can work in an adaptive way.Expand Abstract
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