Reviews: DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial Learning

This paper proposes a novel method for optimal exposure operation in low quality images. The method uses reinforcement learning coupled with a discriminant loss (from GANs) to learn the optimal sequence of operations (i.e., the different exposures for each subimage component from a semantic segmentation of the input image) that generate, through a blender of all the components, a good quality - better exposed image. The main concern with this paper is the poor clarity of exposition. The formal definition of the image processing problem is lacking. Semantic segmentation is one major component but it's not discussed.