Yang, Q., Yang, G., Jiang, J., Li, C., Feng, R., Zhou, S., Sun, W., Zhu, Q., Loy, C. C., Gu, J., Wang, Z., Li, D., Zhang, Y., Peng, L., Chang, X., Zhang, Y., Bian, L., Li, B., Huang, J., ... Liu, S. (2023). MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report. 在 L. Karlinsky, T. Michaeli, & K. Nishino (编辑), Computer Vision - ECCV 2022 Workshops, Proceedings (页码 46-59). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 13805 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-25072-9_4
@inproceedings{a48404572a5941eb91e4aa5d60c8e27e,
title = "MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report",
abstract = "Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, RGBW Joint Fusion and Denoise, one of the five tracks, working on the fusion of binning-mode RGBW to Bayer at half resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality RGBW and Bayer pair. In addition, for each scene, RGBW of 24 dB and 42 dB are provided. All the data were captured using a RGBW sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [11], LPIPS [15] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022",
keywords = "Bayer, Denoise, Fusion, MIPI challenge, RGBW",
author = "Qingyu Yang and Guang Yang and Jun Jiang and Chongyi Li and Ruicheng Feng and Shangchen Zhou and Wenxiu Sun and Qingpeng Zhu and Loy, {Chen Change} and Jinwei Gu and Zhen Wang and Daoyu Li and Yuzhe Zhang and Lintao Peng and Xuyang Chang and Yinuo Zhang and Liheng Bian and Bing Li and Jie Huang and Mingde Yao and Ruikang Xu and Feng Zhao and Xiaohui Liu and Rongjian Xu and Zhilu Zhang and Xiaohe Wu and Ruohao Wang and Junyi Li and Wangmeng Zuo and Zhuang Jia and Lee, {Dong Jae} and Ting Jiang and Qi Wu and Chengzhi Jiang and Mingyan Han and Xinpeng Li and Wenjie Lin and Youwei Li and Haoqiang Fan and Shuaicheng Liu",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 17th European Conference on Computer Vision, ECCV 2022 ; Conference date: 23-10-2022 Through 27-10-2022",
year = "2023",
doi = "10.1007/978-3-031-25072-9_4",
language = "English",
isbn = "9783031250712",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "46--59",
editor = "Leonid Karlinsky and Tomer Michaeli and Ko Nishino",
booktitle = "Computer Vision - ECCV 2022 Workshops, Proceedings",
address = "Germany",
}
Yang, Q, Yang, G, Jiang, J, Li, C, Feng, R, Zhou, S, Sun, W, Zhu, Q, Loy, CC, Gu, J, Wang, Z, Li, D, Zhang, Y, Peng, L, Chang, X, Zhang, Y, Bian, L, Li, B, Huang, J, Yao, M, Xu, R, Zhao, F, Liu, X, Xu, R, Zhang, Z, Wu, X, Wang, R, Li, J, Zuo, W, Jia, Z, Lee, DJ, Jiang, T, Wu, Q, Jiang, C, Han, M, Li, X, Lin, W, Li, Y, Fan, H & Liu, S 2023, MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report. 在 L Karlinsky, T Michaeli & K Nishino (编辑), Computer Vision - ECCV 2022 Workshops, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 13805 LNCS, Springer Science and Business Media Deutschland GmbH, 页码 46-59, 17th European Conference on Computer Vision, ECCV 2022, Tel Aviv, 以色列, 23/10/22. https://doi.org/10.1007/978-3-031-25072-9_4
TY - GEN
T1 - MIPI 2022 Challenge on RGBW Sensor Fusion
T2 - 17th European Conference on Computer Vision, ECCV 2022
AU - Yang, Qingyu
AU - Yang, Guang
AU - Jiang, Jun
AU - Li, Chongyi
AU - Feng, Ruicheng
AU - Zhou, Shangchen
AU - Sun, Wenxiu
AU - Zhu, Qingpeng
AU - Loy, Chen Change
AU - Gu, Jinwei
AU - Wang, Zhen
AU - Li, Daoyu
AU - Zhang, Yuzhe
AU - Peng, Lintao
AU - Chang, Xuyang
AU - Zhang, Yinuo
AU - Bian, Liheng
AU - Li, Bing
AU - Huang, Jie
AU - Yao, Mingde
AU - Xu, Ruikang
AU - Zhao, Feng
AU - Liu, Xiaohui
AU - Xu, Rongjian
AU - Zhang, Zhilu
AU - Wu, Xiaohe
AU - Wang, Ruohao
AU - Li, Junyi
AU - Zuo, Wangmeng
AU - Jia, Zhuang
AU - Lee, Dong Jae
AU - Jiang, Ting
AU - Wu, Qi
AU - Jiang, Chengzhi
AU - Han, Mingyan
AU - Li, Xinpeng
AU - Lin, Wenjie
AU - Li, Youwei
AU - Fan, Haoqiang
AU - Liu, Shuaicheng
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, RGBW Joint Fusion and Denoise, one of the five tracks, working on the fusion of binning-mode RGBW to Bayer at half resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality RGBW and Bayer pair. In addition, for each scene, RGBW of 24 dB and 42 dB are provided. All the data were captured using a RGBW sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [11], LPIPS [15] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022
AB - Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, RGBW Joint Fusion and Denoise, one of the five tracks, working on the fusion of binning-mode RGBW to Bayer at half resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality RGBW and Bayer pair. In addition, for each scene, RGBW of 24 dB and 42 dB are provided. All the data were captured using a RGBW sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [11], LPIPS [15] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022
KW - Bayer
KW - Denoise
KW - Fusion
KW - MIPI challenge
KW - RGBW
UR - http://www.scopus.com/inward/record.url?scp=85150953320&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-25072-9_4
DO - 10.1007/978-3-031-25072-9_4
M3 - Conference contribution
AN - SCOPUS:85150953320
SN - 9783031250712
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 46
EP - 59
BT - Computer Vision - ECCV 2022 Workshops, Proceedings
A2 - Karlinsky, Leonid
A2 - Michaeli, Tomer
A2 - Nishino, Ko
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 23 October 2022 through 27 October 2022
ER -
Yang Q, Yang G, Jiang J, Li C, Feng R, Zhou S 等. MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report. 在 Karlinsky L, Michaeli T, Nishino K, 编辑, Computer Vision - ECCV 2022 Workshops, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. 页码 46-59. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-25072-9_4
