NTIRE 2020 challenge on spectral reconstruction from an RGB image

Boaz Arad; Radu Timofte; Ohad Ben-Shahar; Yi Tun Lin; Graham Finlayson; Shai Givati; Jiaojiao Li; Chaoxiong Wu; Rui Song; Yunsong Li; Fei Liu; Zhiqiang Lang; Wei Wei; Lei Zhang; Jiangtao Nie; Yuzhi Zhao; Lai Man Po; Qiong Yan; Wei Liu; Tingyu Lin; Youngjung Kim; Changyeop Shin; Kyeongha Rho; Sungho Kim; Zhiyu Zhu; Junhui Hou; He Sun; Jinchang Ren; Zhenyu Fang; Yijun Yan; Hao Peng; Xiaomei Chen; Jie Zhao; Tarek Stiebel; Simon Koppers; Dorit Merhof; Honey Gupta; Kaushik Mitra; Biebele Joslyn Fubara; Mohamed Sedky; Dave Dyke; Atmadeep Banerjee; Akash Palrecha; Sabarinathan Sabarinathan; K. Uma; D. Synthiya Vinothini; B. Sathya Bama; S. M. Md Mansoor Roomi

doi:10.1109/CVPRW50498.2020.00231

NTIRE 2020 challenge on spectral reconstruction from an RGB image

Boaz Arad, Radu Timofte, Ohad Ben-Shahar, Yi Tun Lin, Graham Finlayson, Shai Givati, Jiaojiao Li, Chaoxiong Wu, Rui Song, Yunsong Li, Fei Liu, Zhiqiang Lang, Wei Wei, Lei Zhang, Jiangtao Nie, Yuzhi Zhao, Lai Man Po, Qiong Yan, Wei Liu, Tingyu LinYoungjung Kim, Changyeop Shin, Kyeongha Rho, Sungho Kim, Zhiyu Zhu, Junhui Hou, He Sun, Jinchang Ren, Zhenyu Fang, Yijun Yan, Hao Peng, Xiaomei Chen, Jie Zhao, Tarek Stiebel, Simon Koppers, Dorit Merhof, Honey Gupta, Kaushik Mitra, Biebele Joslyn Fubara, Mohamed Sedky, Dave Dyke, Atmadeep Banerjee, Akash Palrecha, Sabarinathan Sabarinathan, K. Uma, D. Synthiya Vinothini, B. Sathya Bama, S. M. Md Mansoor Roomi

Department of Computer Science

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

147 Scopus citations

Abstract

This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole- scene hyperspectral (HS) information from a 3-channel RGB image. As in the previous challenge, two tracks were provided: (i) a "Clean" track where HS images are estimated from noise-free RGBs, the RGB images are themselves calculated numerically using the ground-truth HS images and supplied spectral sensitivity functions (ii) a "Real World" track, simulating capture by an uncalibrated and unknown camera, where the HS images are recovered from noisy JPEG-compressed RGB images. A new, larger-than-ever, natural hyperspectral image data set is presented, containing a total of 510 HS images. The Clean and Real World tracks had 103 and 78 registered participants respectively, with 14 teams competing in the final testing phase. A description of the proposed methods, alongside their challenge scores and an extensive evaluation of top performing methods is also provided. They gauge the state-of-the-art in spectral reconstruction from an RGB image.

Original language	English
Title of host publication	Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Publisher	Institute of Electrical and Electronics Engineers
Pages	1806-1822
Number of pages	17
ISBN (Electronic)	9781728193601
DOIs	https://doi.org/10.1109/CVPRW50498.2020.00231
State	Published - 1 Jun 2020
Event	2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 - Virtual, Online, United States Duration: 14 Jun 2020 → 19 Jun 2020

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2020-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Country/Territory	United States
City	Virtual, Online
Period	14/06/20 → 19/06/20

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

Access to Document

10.1109/CVPRW50498.2020.00231

Cite this

Arad, B., Timofte, R., Ben-Shahar, O., Lin, Y. T., Finlayson, G., Givati, S., Li, J., Wu, C., Song, R., Li, Y., Liu, F., Lang, Z., Wei, W., Zhang, L., Nie, J., Zhao, Y., Po, L. M., Yan, Q., Liu, W., ... Md Mansoor Roomi, S. M. (2020). NTIRE 2020 challenge on spectral reconstruction from an RGB image. In Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 (pp. 1806-1822). Article 9150756 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2020-June). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CVPRW50498.2020.00231

Arad, Boaz ; Timofte, Radu ; Ben-Shahar, Ohad et al. / NTIRE 2020 challenge on spectral reconstruction from an RGB image. Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020. Institute of Electrical and Electronics Engineers, 2020. pp. 1806-1822 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

@inproceedings{661410a1b280418b984a6bd523580d81,

title = "NTIRE 2020 challenge on spectral reconstruction from an RGB image",

abstract = "This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole- scene hyperspectral (HS) information from a 3-channel RGB image. As in the previous challenge, two tracks were provided: (i) a {"}Clean{"} track where HS images are estimated from noise-free RGBs, the RGB images are themselves calculated numerically using the ground-truth HS images and supplied spectral sensitivity functions (ii) a {"}Real World{"} track, simulating capture by an uncalibrated and unknown camera, where the HS images are recovered from noisy JPEG-compressed RGB images. A new, larger-than-ever, natural hyperspectral image data set is presented, containing a total of 510 HS images. The Clean and Real World tracks had 103 and 78 registered participants respectively, with 14 teams competing in the final testing phase. A description of the proposed methods, alongside their challenge scores and an extensive evaluation of top performing methods is also provided. They gauge the state-of-the-art in spectral reconstruction from an RGB image.",

author = "Boaz Arad and Radu Timofte and Ohad Ben-Shahar and Lin, {Yi Tun} and Graham Finlayson and Shai Givati and Jiaojiao Li and Chaoxiong Wu and Rui Song and Yunsong Li and Fei Liu and Zhiqiang Lang and Wei Wei and Lei Zhang and Jiangtao Nie and Yuzhi Zhao and Po, {Lai Man} and Qiong Yan and Wei Liu and Tingyu Lin and Youngjung Kim and Changyeop Shin and Kyeongha Rho and Sungho Kim and Zhiyu Zhu and Junhui Hou and He Sun and Jinchang Ren and Zhenyu Fang and Yijun Yan and Hao Peng and Xiaomei Chen and Jie Zhao and Tarek Stiebel and Simon Koppers and Dorit Merhof and Honey Gupta and Kaushik Mitra and Fubara, {Biebele Joslyn} and Mohamed Sedky and Dave Dyke and Atmadeep Banerjee and Akash Palrecha and Sabarinathan Sabarinathan and K. Uma and Vinothini, {D. Synthiya} and {Sathya Bama}, B. and {Md Mansoor Roomi}, {S. M.}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 ; Conference date: 14-06-2020 Through 19-06-2020",

year = "2020",

month = jun,

day = "1",

doi = "10.1109/CVPRW50498.2020.00231",

language = "English",

series = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",

publisher = "Institute of Electrical and Electronics Engineers",

pages = "1806--1822",

booktitle = "Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020",

address = "United States",

}

Arad, B, Timofte, R, Ben-Shahar, O, Lin, YT, Finlayson, G, Givati, S, Li, J, Wu, C, Song, R, Li, Y, Liu, F, Lang, Z, Wei, W, Zhang, L, Nie, J, Zhao, Y, Po, LM, Yan, Q, Liu, W, Lin, T, Kim, Y, Shin, C, Rho, K, Kim, S, Zhu, Z, Hou, J, Sun, H, Ren, J, Fang, Z, Yan, Y, Peng, H, Chen, X, Zhao, J, Stiebel, T, Koppers, S, Merhof, D, Gupta, H, Mitra, K, Fubara, BJ, Sedky, M, Dyke, D, Banerjee, A, Palrecha, A, Sabarinathan, S, Uma, K, Vinothini, DS, Sathya Bama, B & Md Mansoor Roomi, SM 2020, NTIRE 2020 challenge on spectral reconstruction from an RGB image. in Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020., 9150756, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2020-June, Institute of Electrical and Electronics Engineers, pp. 1806-1822, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020, Virtual, Online, United States, 14/06/20. https://doi.org/10.1109/CVPRW50498.2020.00231

NTIRE 2020 challenge on spectral reconstruction from an RGB image. / Arad, Boaz; Timofte, Radu; Ben-Shahar, Ohad et al.
Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020. Institute of Electrical and Electronics Engineers, 2020. p. 1806-1822 9150756 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2020-June).

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

TY - GEN

T1 - NTIRE 2020 challenge on spectral reconstruction from an RGB image

AU - Arad, Boaz

AU - Timofte, Radu

AU - Ben-Shahar, Ohad

AU - Lin, Yi Tun

AU - Finlayson, Graham

AU - Givati, Shai

AU - Li, Jiaojiao

AU - Wu, Chaoxiong

AU - Song, Rui

AU - Li, Yunsong

AU - Liu, Fei

AU - Lang, Zhiqiang

AU - Wei, Wei

AU - Zhang, Lei

AU - Nie, Jiangtao

AU - Zhao, Yuzhi

AU - Po, Lai Man

AU - Yan, Qiong

AU - Liu, Wei

AU - Lin, Tingyu

AU - Kim, Youngjung

AU - Shin, Changyeop

AU - Rho, Kyeongha

AU - Kim, Sungho

AU - Zhu, Zhiyu

AU - Hou, Junhui

AU - Sun, He

AU - Ren, Jinchang

AU - Fang, Zhenyu

AU - Yan, Yijun

AU - Peng, Hao

AU - Chen, Xiaomei

AU - Zhao, Jie

AU - Stiebel, Tarek

AU - Koppers, Simon

AU - Merhof, Dorit

AU - Gupta, Honey

AU - Mitra, Kaushik

AU - Fubara, Biebele Joslyn

AU - Sedky, Mohamed

AU - Dyke, Dave

AU - Banerjee, Atmadeep

AU - Palrecha, Akash

AU - Sabarinathan, Sabarinathan

AU - Uma, K.

AU - Vinothini, D. Synthiya

AU - Sathya Bama, B.

AU - Md Mansoor Roomi, S. M.

PY - 2020/6/1

Y1 - 2020/6/1

N2 - This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole- scene hyperspectral (HS) information from a 3-channel RGB image. As in the previous challenge, two tracks were provided: (i) a "Clean" track where HS images are estimated from noise-free RGBs, the RGB images are themselves calculated numerically using the ground-truth HS images and supplied spectral sensitivity functions (ii) a "Real World" track, simulating capture by an uncalibrated and unknown camera, where the HS images are recovered from noisy JPEG-compressed RGB images. A new, larger-than-ever, natural hyperspectral image data set is presented, containing a total of 510 HS images. The Clean and Real World tracks had 103 and 78 registered participants respectively, with 14 teams competing in the final testing phase. A description of the proposed methods, alongside their challenge scores and an extensive evaluation of top performing methods is also provided. They gauge the state-of-the-art in spectral reconstruction from an RGB image.

AB - This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole- scene hyperspectral (HS) information from a 3-channel RGB image. As in the previous challenge, two tracks were provided: (i) a "Clean" track where HS images are estimated from noise-free RGBs, the RGB images are themselves calculated numerically using the ground-truth HS images and supplied spectral sensitivity functions (ii) a "Real World" track, simulating capture by an uncalibrated and unknown camera, where the HS images are recovered from noisy JPEG-compressed RGB images. A new, larger-than-ever, natural hyperspectral image data set is presented, containing a total of 510 HS images. The Clean and Real World tracks had 103 and 78 registered participants respectively, with 14 teams competing in the final testing phase. A description of the proposed methods, alongside their challenge scores and an extensive evaluation of top performing methods is also provided. They gauge the state-of-the-art in spectral reconstruction from an RGB image.

UR - http://www.scopus.com/inward/record.url?scp=85089667281&partnerID=8YFLogxK

U2 - 10.1109/CVPRW50498.2020.00231

DO - 10.1109/CVPRW50498.2020.00231

M3 - Conference contribution

AN - SCOPUS:85089667281

T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

SP - 1806

EP - 1822

BT - Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020

PB - Institute of Electrical and Electronics Engineers

T2 - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020

Y2 - 14 June 2020 through 19 June 2020

ER -

Arad B, Timofte R, Ben-Shahar O, Lin YT, Finlayson G, Givati S et al. NTIRE 2020 challenge on spectral reconstruction from an RGB image. In Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020. Institute of Electrical and Electronics Engineers. 2020. p. 1806-1822. 9150756. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW50498.2020.00231

NTIRE 2020 challenge on spectral reconstruction from an RGB image

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