Options
AIM 2020 Challenge on Rendering Realistic Bokeh
Date Issued
01-01-2020
Author(s)
Ignatov, Andrey
Timofte, Radu
Qian, Ming
Qiao, Congyu
Lin, Jiamin
Guo, Zhenyu
Li, Chenghua
Leng, Cong
Cheng, Jian
Peng, Juewen
Luo, Xianrui
Xian, Ke
Wu, Zijin
Cao, Zhiguo
Puthussery, Densen
Jiji, C. V.
Hrishikesh, P. S.
Kuriakose, Melvin
Dutta, Saikat
Das, Sourya Dipta
Shah, Nisarg A.
Purohit, Kuldeep
Kandula, Praveen
Suin, Maitreya
Indian Institute of Technology, Madras
Saagara, M. B.
Minnu, A. L.
Sanjana, A. R.
Praseeda, S.
Wu, Ge
Chen, Xueqin
Wang, Tengyao
Zheng, Max
Wong, Hulk
Zou, Jay
Abstract
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.
Volume
12537 LNCS