RefineDNet: A Weakly Supervised Refinement Framework for Single Image Dehazing.Haze-free images are the prerequisites of many vision systems and algorithms, and thus single image dehazing is of paramount importance in computer vision.  Specifically, we propose a two-stage weakly supervised dehazing framework, RefineDNet.  In the first stage, RefineDNet adopts the dark channel prior to restore visibility.  Extensive experiments corroborate that RefineDNet with the perceptual fusion has an outstanding haze removal capability and can also produce visually pleasing results.  Even implemented with basic backbone networks, RefineDNet can outperform supervised dehazing approaches as well as other state-of-the-art methods on indoor and outdoor datasets.  To make our results reproducible, relevant code and data are available at https://github.com/xiaofeng94/RefineDNet-for-dehazing.
RefineDNet