EnlightenGAN: Deep Light Enhancement without Paired Supervision

Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data? As one such example, this paper explores the low-light image enhancement problem, where in practice it is extremely challenging to simultaneously take a low-light and a normal-light photo of the same visual scene... (read more)

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Datasets


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Low-Light Image Enhancement AFLW (Zhang CVPR 2018 crops) enligh 14 gestures accuracy 1 # 1
Low-Light Image Enhancement DICM EnlightenGAN User Study Score 3.50 # 2
Low-Light Image Enhancement MEF EnlightenGAN User Study Score 3.75 # 2
Low-Light Image Enhancement VV EnlightenGAN User Study Score 3.17 # 2

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet