Abstract:In recent years, learning-based low-light image enhancement methods have shown excellent performance, but the heuristic design adopted by most methods requires high engineering skills for developers, causing expensive inference costs that are unfriendly to the hardware platform. To handle this issue, we propose to automatically discover an efficient architecture, called progressive attentive Retinex network (PAR-Net). We define a new attentive Retinex framework by introducing the attention mechanism to strengt… Show more
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