  This paper reviews the NTIRE 2022 challenge on efficient single image
super-resolution with focus on the proposed solutions and results. The task of
the challenge was to super-resolve an input image with a magnification factor
of $\times$4 based on pairs of low and corresponding high resolution images.
The aim was to design a network for single image super-resolution that achieved
improvement of efficiency measured according to several metrics including
runtime, parameters, FLOPs, activations, and memory consumption while at least
maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the
baseline for efficiency measurement. The challenge had 3 tracks including the
main track (runtime), sub-track one (model complexity), and sub-track two
(overall performance). In the main track, the practical runtime performance of
the submissions was evaluated. The rank of the teams were determined directly
by the absolute value of the average runtime on the validation set and test
set. In sub-track one, the number of parameters and FLOPs were considered. And
the individual rankings of the two metrics were summed up to determine a final
ranking in this track. In sub-track two, all of the five metrics mentioned in
the description of the challenge including runtime, parameter count, FLOPs,
activations, and memory consumption were considered. Similar to sub-track one,
the rankings of five metrics were summed up to determine a final ranking. The
challenge had 303 registered participants, and 43 teams made valid submissions.
They gauge the state-of-the-art in efficient single image super-resolution.
