  This paper reviews the NTIRE 2020 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 along with a set of unpaired high-quality target images. In
Track 1: Image Processing artifacts, the aim is to super-resolve images with
synthetically generated image processing artifacts. This allows for
quantitative benchmarking of the approaches \wrt a ground-truth image. In Track
2: Smartphone Images, real low-quality smart phone images have to be
super-resolved. In both tracks, the ultimate goal is to achieve the best
perceptual quality, evaluated using a human study. This is the second challenge
on the subject, following AIM 2019, targeting to advance the state-of-the-art
in super-resolution. To measure the performance we use the benchmark protocol
from AIM 2019. In total 22 teams competed in the final testing phase,
demonstrating new and innovative solutions to the problem.
