  This paper reports on the 2018 PIRM challenge on perceptual super-resolution
(SR), held in conjunction with the Perceptual Image Restoration and
Manipulation (PIRM) workshop at ECCV 2018. In contrast to previous SR
challenges, our evaluation methodology jointly quantifies accuracy and
perceptual quality, therefore enabling perceptual-driven methods to compete
alongside algorithms that target PSNR maximization. Twenty-one participating
teams introduced algorithms which well-improved upon the existing
state-of-the-art methods in perceptual SR, as confirmed by a human opinion
study. We also analyze popular image quality measures and draw conclusions
regarding which of them correlates best with human opinion scores. We conclude
with an analysis of the current trends in perceptual SR, as reflected from the
leading submissions.
