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.
Original language | English |
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Title of host publication | Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 3584-3590 |
Number of pages | 7 |
ISBN (Electronic) | 9781728150239 |
DOIs | |
Publication status | Published - 2019 Oct |
Event | 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 - Seoul, Korea, Republic of Duration: 2019 Oct 27 → 2019 Oct 28 |
Publication series
Name | Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 |
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Conference
Conference | 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 19/10/27 → 19/10/28 |
Keywords
- AIM
- AIM2019
- Challenge
- Computer vision
- Deep learning
- Image enhancement
- Image manipulation
- Mobile cameras
- RAW to RGB
- Smartphones
ASJC Scopus subject areas
- Computer Science Applications
- Computer Vision and Pattern Recognition