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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

30 Scopus citations


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 languageEnglish
Title of host publicationProceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
PublisherInstitute of Electrical and Electronics Engineers
Number of pages19
ISBN (Electronic)9781665487399
StatePublished - 1 Jan 2022
Externally publishedYes
Event2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 - New Orleans, United States
Duration: 19 Jun 202220 Jun 2022

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516


Conference2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Country/TerritoryUnited States
CityNew Orleans

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


Dive into the research topics of 'NTIRE 2022 Spectral Recovery Challenge and Data Set'. Together they form a unique fingerprint.

Cite this