AIM 2020 Challenge on Rendering Realistic Bokeh
This addresses the problem of realistic bokeh simulation for photography and image processing applications, but it is incremental as it builds on existing challenges and datasets.
The paper reviews a challenge on rendering realistic bokeh effects, where participants used a dataset of 5K image pairs to learn shallow focus techniques, achieving significant improvements over baseline results and setting a new state-of-the-art.
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.