Learning to See in the Dark

@article{Chen2018LearningTS,
  title={Learning to See in the Dark},
  author={Chen Chen and Qifeng Chen and Jia Xu and Vladlen Koltun},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={3291-3300}
}
  • Chen Chen, Qifeng Chen, V. Koltun
  • Published 4 May 2018
  • Computer Science
  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Imaging in low light is challenging due to low photon count and low SNR. [] Key Method Using the presented dataset, we develop a pipeline for processing low-light images, based on end-to-end training of a fully-convolutional network. The network operates directly on raw sensor data and replaces much of the traditional image processing pipeline, which tends to perform poorly on such data. We report promising results on the new dataset, analyze factors that affect performance, and highlight opportunities for…
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