  This paper reviews the AIM 2019 challenge on real world super-resolution. It
focuses on the participating methods and final results. The challenge addresses
the real world setting, where paired true high and low-resolution images are
unavailable. For training, only one set of source input images is therefore
provided in the challenge. In Track 1: Source Domain the aim is to
super-resolve such images while preserving the low level image characteristics
of the source input domain. In Track 2: Target Domain a set of high-quality
images is also provided for training, that defines the output domain and
desired quality of the super-resolved images. To allow for quantitative
evaluation, the source input images in both tracks are constructed using
artificial, but realistic, image degradations. The challenge is the first of
its kind, aiming to advance the state-of-the-art and provide a standard
benchmark for this newly emerging task. In total 7 teams competed in the final
testing phase, demonstrating new and innovative solutions to the problem.
