NTIRE 2022 Spectral Recovery Challenge and Data Set

Boaz Arad; Radu Timofte; Rony Yahel; Nimrod Morag; Amir Bernat; Yuanhao Cai; Jing Lin; Zudi Lin; Haoqian Wang; Yulun Zhang; Hanspeter Pfister; Luc Van Gool; Shuai Liu; Yongqiang Li; Chaoyu Feng; Lei Lei; Jiaojiao Li; Songcheng Du; Chaoxiong Wu; Yihong Leng; Rui Song; Mingwei Zhang; Chongxing Song; Shuyi Zhao; Zhiqiang Lang; Wei Wei; Lei Zhang; Renwei Dian; Tianci Shan; Anjing Guo; Chengguo Feng; Jinyang Liu; Mirko Agarla; Simone Bianco; Marco Buzzelli; Luigi Celona; Raimondo Schettini; Jiang He; Yi Xiao; Jiajun Xiao; Qiangqiang Yuan; Jie Li; Liangpei Zhang; Taesung Kwon; Dohoon Ryu; Hyokyoung Bae; Hao Hsiang Yang; Hua En Chang; Zhi Kai Huang; Wei Ting Chen; Sy Yen Kuo; Junyu Chen; Haiwei Li; Song Liu; Sabarinathan Sabarinathan; K. Uma; B. Sathya Bama; S. Mohamed Mansoor Roomi

doi:10.1109/CVPRW56347.2022.00102

NTIRE 2022 Spectral Recovery Challenge and Data Set

Boaz Arad, Radu Timofte, Rony Yahel, Nimrod Morag, Amir Bernat, Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Luc Van Gool, Shuai Liu, Yongqiang Li, Chaoyu Feng, Lei Lei, Jiaojiao Li, Songcheng Du, Chaoxiong Wu, Yihong LengRui Song, Mingwei Zhang, Chongxing Song, Shuyi Zhao, Zhiqiang Lang, Wei Wei, Lei Zhang, Renwei Dian, Tianci Shan, Anjing Guo, Chengguo Feng, Jinyang Liu, Mirko Agarla, Simone Bianco, Marco Buzzelli, Luigi Celona, Raimondo Schettini, Jiang He, Yi Xiao, Jiajun Xiao, Qiangqiang Yuan, Jie Li, Liangpei Zhang, Taesung Kwon, Dohoon Ryu, Hyokyoung Bae, Hao Hsiang Yang, Hua En Chang, Zhi Kai Huang, Wei Ting Chen, Sy Yen Kuo, Junyu Chen, Haiwei Li, Song Liu, Sabarinathan Sabarinathan, K. Uma, B. Sathya Bama, S. Mohamed Mansoor Roomi

School of Computer Science

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

123 Scopus citations

Abstract

This paper reviews the third biennial challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. This challenge presents the "ARAD_1K"data set: a new, larger-than-ever natural hyperspectral image data set containing 1,000 images. Challenge participants were required to recover hyper-spectral information from synthetically generated JPEG-compressed RGB images simulating capture by a known calibrated camera, operating under partially known parameters, in a setting which includes acquisition noise. The challenge was attended by 241 teams, with 60 teams com-peting in the final testing phase, 12 of which provided de-tailed descriptions of their methodology which are included in this report. The performance of these submissions is re-viewed and provided here as a gauge for the current state-of-the-art in spectral reconstruction from natural RGB images.

Original language	English
Title of host publication	Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Publisher	IEEE Computer Society
Pages	862-880
Number of pages	19
ISBN (Electronic)	9781665487399
DOIs	https://doi.org/10.1109/CVPRW56347.2022.00102
State	Published - 2022
Event	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 - New Orleans, United States Duration: 19 Jun 2022 → 24 Jun 2022

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2022-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Country/Territory	United States
City	New Orleans
Period	19/06/22 → 24/06/22

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10.1109/CVPRW56347.2022.00102

Cite this

Arad, B., Timofte, R., Yahel, R., Morag, N., Bernat, A., Cai, Y., Lin, J., Lin, Z., Wang, H., Zhang, Y., Pfister, H., Van Gool, L., Liu, S., Li, Y., Feng, C., Lei, L., Li, J., Du, S., Wu, C., ... Roomi, S. M. M. (2022). NTIRE 2022 Spectral Recovery Challenge and Data Set. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 (pp. 862-880). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW56347.2022.00102

@inproceedings{5b7a2a534dd34bb6b2bcc096d8e64391,

title = "NTIRE 2022 Spectral Recovery Challenge and Data Set",

abstract = "This paper reviews the third biennial challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. This challenge presents the {"}ARAD_1K{"}data set: a new, larger-than-ever natural hyperspectral image data set containing 1,000 images. Challenge participants were required to recover hyper-spectral information from synthetically generated JPEG-compressed RGB images simulating capture by a known calibrated camera, operating under partially known parameters, in a setting which includes acquisition noise. The challenge was attended by 241 teams, with 60 teams com-peting in the final testing phase, 12 of which provided de-tailed descriptions of their methodology which are included in this report. The performance of these submissions is re-viewed and provided here as a gauge for the current state-of-the-art in spectral reconstruction from natural RGB images.",

author = "Boaz Arad and Radu Timofte and Rony Yahel and Nimrod Morag and Amir Bernat and Yuanhao Cai and Jing Lin and Zudi Lin and Haoqian Wang and Yulun Zhang and Hanspeter Pfister and {Van Gool}, Luc and Shuai Liu and Yongqiang Li and Chaoyu Feng and Lei Lei and Jiaojiao Li and Songcheng Du and Chaoxiong Wu and Yihong Leng and Rui Song and Mingwei Zhang and Chongxing Song and Shuyi Zhao and Zhiqiang Lang and Wei Wei and Lei Zhang and Renwei Dian and Tianci Shan and Anjing Guo and Chengguo Feng and Jinyang Liu and Mirko Agarla and Simone Bianco and Marco Buzzelli and Luigi Celona and Raimondo Schettini and Jiang He and Yi Xiao and Jiajun Xiao and Qiangqiang Yuan and Jie Li and Liangpei Zhang and Taesung Kwon and Dohoon Ryu and Hyokyoung Bae and Yang, {Hao Hsiang} and Chang, {Hua En} and Huang, {Zhi Kai} and Chen, {Wei Ting} and Kuo, {Sy Yen} and Junyu Chen and Haiwei Li and Song Liu and Sabarinathan Sabarinathan and K. Uma and Bama, {B. Sathya} and Roomi, {S. Mohamed Mansoor}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 ; Conference date: 19-06-2022 Through 24-06-2022",

year = "2022",

doi = "10.1109/CVPRW56347.2022.00102",

language = "英语",

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

publisher = "IEEE Computer Society",

pages = "862--880",

booktitle = "Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022",

}

Arad, B, Timofte, R, Yahel, R, Morag, N, Bernat, A, Cai, Y, Lin, J, Lin, Z, Wang, H, Zhang, Y, Pfister, H, Van Gool, L, Liu, S, Li, Y, Feng, C, Lei, L, Li, J, Du, S, Wu, C, Leng, Y, Song, R, Zhang, M, Song, C, Zhao, S, Lang, Z, Wei, W , Zhang, L, Dian, R, Shan, T, Guo, A, Feng, C, Liu, J, Agarla, M, Bianco, S, Buzzelli, M, Celona, L, Schettini, R, He, J, Xiao, Y, Xiao, J, Yuan, Q, Li, J, Zhang, L, Kwon, T, Ryu, D, Bae, H, Yang, HH, Chang, HE, Huang, ZK, Chen, WT, Kuo, SY, Chen, J, Li, H, Liu, S, Sabarinathan, S, Uma, K, Bama, BS & Roomi, SMM 2022, NTIRE 2022 Spectral Recovery Challenge and Data Set. in Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2022-June, IEEE Computer Society, pp. 862-880, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022, New Orleans, United States, 19/06/22. https://doi.org/10.1109/CVPRW56347.2022.00102

NTIRE 2022 Spectral Recovery Challenge and Data Set. / Arad, Boaz; Timofte, Radu; Yahel, Rony et al.
Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society, 2022. p. 862-880 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June).

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

TY - GEN

T1 - NTIRE 2022 Spectral Recovery Challenge and Data Set

AU - Arad, Boaz

AU - Timofte, Radu

AU - Yahel, Rony

AU - Morag, Nimrod

AU - Bernat, Amir

AU - Cai, Yuanhao

AU - Lin, Jing

AU - Lin, Zudi

AU - Wang, Haoqian

AU - Zhang, Yulun

AU - Pfister, Hanspeter

AU - Van Gool, Luc

AU - Liu, Shuai

AU - Li, Yongqiang

AU - Feng, Chaoyu

AU - Lei, Lei

AU - Li, Jiaojiao

AU - Du, Songcheng

AU - Wu, Chaoxiong

AU - Leng, Yihong

AU - Song, Rui

AU - Zhang, Mingwei

AU - Song, Chongxing

AU - Zhao, Shuyi

AU - Lang, Zhiqiang

AU - Wei, Wei

AU - Zhang, Lei

AU - Dian, Renwei

AU - Shan, Tianci

AU - Guo, Anjing

AU - Feng, Chengguo

AU - Liu, Jinyang

AU - Agarla, Mirko

AU - Bianco, Simone

AU - Buzzelli, Marco

AU - Celona, Luigi

AU - Schettini, Raimondo

AU - He, Jiang

AU - Xiao, Yi

AU - Xiao, Jiajun

AU - Yuan, Qiangqiang

AU - Li, Jie

AU - Zhang, Liangpei

AU - Kwon, Taesung

AU - Ryu, Dohoon

AU - Bae, Hyokyoung

AU - Yang, Hao Hsiang

AU - Chang, Hua En

AU - Huang, Zhi Kai

AU - Chen, Wei Ting

AU - Kuo, Sy Yen

AU - Chen, Junyu

AU - Li, Haiwei

AU - Liu, Song

AU - Sabarinathan, Sabarinathan

AU - Uma, K.

AU - Bama, B. Sathya

AU - Roomi, S. Mohamed Mansoor

PY - 2022

Y1 - 2022

N2 - This paper reviews the third biennial challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. This challenge presents the "ARAD_1K"data set: a new, larger-than-ever natural hyperspectral image data set containing 1,000 images. Challenge participants were required to recover hyper-spectral information from synthetically generated JPEG-compressed RGB images simulating capture by a known calibrated camera, operating under partially known parameters, in a setting which includes acquisition noise. The challenge was attended by 241 teams, with 60 teams com-peting in the final testing phase, 12 of which provided de-tailed descriptions of their methodology which are included in this report. The performance of these submissions is re-viewed and provided here as a gauge for the current state-of-the-art in spectral reconstruction from natural RGB images.

AB - This paper reviews the third biennial challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. This challenge presents the "ARAD_1K"data set: a new, larger-than-ever natural hyperspectral image data set containing 1,000 images. Challenge participants were required to recover hyper-spectral information from synthetically generated JPEG-compressed RGB images simulating capture by a known calibrated camera, operating under partially known parameters, in a setting which includes acquisition noise. The challenge was attended by 241 teams, with 60 teams com-peting in the final testing phase, 12 of which provided de-tailed descriptions of their methodology which are included in this report. The performance of these submissions is re-viewed and provided here as a gauge for the current state-of-the-art in spectral reconstruction from natural RGB images.

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U2 - 10.1109/CVPRW56347.2022.00102

DO - 10.1109/CVPRW56347.2022.00102

M3 - 会议稿件

AN - SCOPUS:85137832328

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

SP - 862

EP - 880

BT - Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022

PB - IEEE Computer Society

T2 - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022

Y2 - 19 June 2022 through 24 June 2022

ER -

Arad B, Timofte R, Yahel R, Morag N, Bernat A, Cai Y et al. NTIRE 2022 Spectral Recovery Challenge and Data Set. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society. 2022. p. 862-880. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW56347.2022.00102

NTIRE 2022 Spectral Recovery Challenge and Data Set

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