  This paper reviews the second AIM realistic bokeh effect rendering challenge
and provides the description of the proposed solutions and results. The
participating teams were solving a real-world bokeh simulation problem, where
the goal was to learn a realistic shallow focus technique using a large-scale
EBB! bokeh dataset consisting of 5K shallow / wide depth-of-field image pairs
captured using the Canon 7D DSLR camera. The participants had to render bokeh
effect based on only one single frame without any additional data from other
cameras or sensors. The target metric used in this challenge combined the
runtime and the perceptual quality of the solutions measured in the user study.
To ensure the efficiency of the submitted models, we measured their runtime on
standard desktop CPUs as well as were running the models on smartphone GPUs.
The proposed solutions significantly improved the baseline results, defining
the state-of-the-art for practical bokeh effect rendering problem.
