AIM 2019 challenge on RAW to RGB mapping: Methods and results

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; Yuzhi Zhao; Lai Man Po; Tiantian Zhang; Zongbang Liao; Xiang Shi; Yujia Zhang; Weifeng Ou; Pengfei Xian; Jingjing Xiong; Chang Zhou; Wing Yin; Yu Yubin; Bingxin Hou; Bumjun Park; Songhyun Yu; Sangmin Kim; Jechang Jeong

doi:10.1109/ICCVW.2019.00443

AIM 2019 challenge on RAW to RGB mapping: Methods and results

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, Yuzhi Zhao, Lai Man Po, Tiantian ZhangZongbang Liao, Xiang Shi, Yujia Zhang, Weifeng Ou, Pengfei Xian, Jingjing Xiong, Chang Zhou, Wing Yin, Yu Yubin, Bingxin Hou, Bumjun Park, Songhyun Yu, Sangmin Kim, Jechang Jeong

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

30 Citations (Scopus)

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
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	https://doi.org/10.1109/ICCVW.2019.00443
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

Conference

Conference	17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019
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

Access to Document

10.1109/ICCVW.2019.00443

Cite this

Ignatov, A., Timofte, R., Jea Ko, S., Kim, S. W., Uhm, K. H., Ji, S. W., Cho, S. J., Hong, J. P., Mei, K., Li, J., Zhang, J., Wu, H., Li, J., Huang, R., Haris, M., Shakhnarovich, G., Ukita, N., Zhao, Y., Po, L. M., ... Jeong, J. (2019). AIM 2019 challenge on RAW to RGB mapping: Methods and results. In Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 (pp. 3584-3590). Article 9022218 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2019.00443

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ignatov, A, Timofte, R, Jea Ko, S, Kim, SW, Uhm, KH, Ji, SW, Cho, SJ, Hong, JP, Mei, K, Li, J, Zhang, J, Wu, H, Li, J, Huang, R, Haris, M, Shakhnarovich, G, Ukita, N, Zhao, Y, Po, LM, Zhang, T, Liao, Z, Shi, X, Zhang, Y, Ou, W, Xian, P, Xiong, J, Zhou, C, Yin, W, Yubin, Y, Hou, B, Park, B, Yu, S, Kim, S & Jeong, J 2019, AIM 2019 challenge on RAW to RGB mapping: Methods and results. in Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019., 9022218, Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019, Institute of Electrical and Electronics Engineers Inc., pp. 3584-3590, 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019, Seoul, Korea, Republic of, 19/10/27. https://doi.org/10.1109/ICCVW.2019.00443

Ignatov A, Timofte R, Jea Ko S, Kim SW, Uhm KH, Ji SW et al. AIM 2019 challenge on RAW to RGB mapping: Methods and results. In Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 3584-3590. 9022218. (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). doi: 10.1109/ICCVW.2019.00443

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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.",

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AIM 2019 challenge on RAW to RGB mapping: Methods and results

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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