AIM 2019 challenge on RAW to RGB mapping: Methods and results
- Authors
- Ignatov, Andrey; Timofte, Radu; Ko, Sung-Jea; Kim, Seung-Wook; Uhm, Kwang-Hyun; Ji, Seo-Won; Cho, Sung-Jin; Hong, Jun-Pyo; Mei, Kangfu; Li, Juncheng; Zhang, Jiajie; Wu, Haoyu; Li, Jie; Huang, Rui; Haris, Muhammad; Shakhnarovich, Greg; Ukita, Norimichi; Zhao, Yuzhi; Po, Lai-Man; Zhang, Tiantian; Liao, Zongbang; Shi, Xiang; Zhang, Yujia; Ou, Weifeng; Xian, Pengfei; Xiong, Jingjing; Zhou, Chang; Yu, Wing Yin; Yubin; Hou, Bingxin; Park, Bumjun; Yu, Songhyun; Kim, Sangmin; Jeong, Jechang
- Issue Date
- Oct-2019
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- AIM; AIM2019; Challenge; Computer vision; Deep learning; Image enhancement; Image manipulation; Mobile cameras; RAW to RGB; Smartphones
- Citation
- Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019, pp.3584 - 3590
- Indexed
- SCOPUS
- Journal Title
- Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019
- Start Page
- 3584
- End Page
- 3590
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/4525
- DOI
- 10.1109/ICCVW.2019.00443
- ISSN
- 2473-9936
- Abstract
- This paper reviews the first AIM challenge on mapping camera RAW to RGB images with the focus on proposed solutions and results. The participating teams were solving a real-world photo enhancement problem, where the goal was to map the original low-quality RAW images from the Huawei P20 device to the same photos captured with the Canon 5D DSLR camera. The considered problem embraced a number of computer vision subtasks, such as image demosaicing, denoising, gamma correction, image resolution and sharpness enhancement, etc. 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 RAW to RGB image restoration.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/4525)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.