AIM 2019 Challenge on RAW to RGB Mapping : Methods and Results

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

36 Scopus Citations
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Author(s)

  • Andrey Ignatov
  • Radu Timofte
  • Sung-Jea Ko
  • Seung-Wook Kim
  • Kwang-Hyun Uhm
  • Seo-Won Ji
  • Sung-Jin Cho
  • Jun-Pyo Hong
  • Kangfu Mei
  • Juncheng Li
  • Jiajie Zhang
  • Haoyu Wu
  • Jie Li
  • Rui Huang
  • Muhammad Haris
  • Greg Shakhnarovich
  • Norimichi Ukita
  • Zongbang Liao
  • Xiang Shi
  • Pengfei Xian
  • Jingjing Xiong
  • Chang Zhou
  • Wing Yin Yu
  • Yubin
  • Bingxin Hou
  • Bumjun Park
  • Songhyun Yu
  • Sangmin Kim
  • Jechang Jeong

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2019 International Conference on Computer Vision, Workshop, ICCV 2019
Subtitle of host publicationProceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages3584-3590
ISBN (electronic)978-1-7281-5023-9
ISBN (print)978-1-7281-5024-6
Publication statusPublished - Oct 2019

Publication series

NameProceedings - International Conference on Computer Vision Workshop, ICCV
ISSN (Print)2473-9936
ISSN (electronic)2473-9944

Conference

Title17th IEEE/CVF International Conference on Computer Vision (ICCV 2019)
LocationCOEX Convention Center
PlaceKorea, Republic of
CitySeoul
Period27 October - 2 November 2019

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.

Research Area(s)

  • AIM, AIM2019, Challenge, Computer vision, Deep learning, Image enhancement, Image manipulation, Mobile cameras, RAW to RGB, Smartphones

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

AIM 2019 Challenge on RAW to RGB Mapping: Methods and Results. / Ignatov, Andrey; Timofte, Radu; Ko, Sung-Jea et al.
2019 International Conference on Computer Vision, Workshop, ICCV 2019: Proceedings. Institute of Electrical and Electronics Engineers, 2019. p. 3584-3590 9022218 (Proceedings - International Conference on Computer Vision Workshop, ICCV).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review