Abstract:Images taken under low light conditions tend to suffer from poor visibility, which can decrease image quality and even reduce the performance of downstream tasks. It is hard for a CNN-based method to learn generalized features that can recover normal images from the ones under various unknown low light conditions. We propose to incorporate the contrastive learning into an illumination correction network to learn abstract representations to distinguish various low light conditions in the representation space, w… Show more
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