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AIM 2019 challenge on bokeh effect synthesis: Methods and results
Date Issued
01-10-2019
Author(s)
Ignatov, Andrey
Patel, Jagruti
Timofte, Radu
Zheng, Bolun
Ye, Xin
Huang, Li
Tian, Xiang
Dutta, Saikat
Purohit, Kuldeep
Kandula, Praveen
Suin, Maitreya
Indian Institute of Technology, Madras
Xiong, Zhiwei
Huang, Jie
Dong, Guanting
Yao, Mingde
Liu, Dong
Yang, Wenjin
Hong, Ming
Lin, Wenying
Qu, Yanyun
Choi, Jae Seok
Park, Woonsung
Kim, Munchurl
Liu, Rui
Mao, Xiangyu
Yang, Chengxi
Yan, Qiong
Sun, Wenxiu
Fang, Junkai
Shang, Meimei
Gao, Fei
Ghosh, Sujoy
Sharma, Prasen Kumar
Sur, Arijit
Abstract
This paper reviews the first AIM challenge on bokeh effect synthesis with the focus on proposed solutions and results. The participating teams were solving a real-world image-to-image mapping problem, where the goal was to map standard narrow-aperture photos to the same photos captured with a shallow depth-of-field by the Canon 70D DSLR camera. In this task, the participants had to restore 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 fidelity scores (PSNR and SSIM) with solutions' perceptual results measured in a user study. The proposed solutions significantly improved baseline results, defining the state-of-the-art for practical bokeh effect simulation.