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NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge

  • Jie Liang
  • , Radu Timofte
  • , Qiaosi Yi
  • , Zhengqiang Zhang
  • , Shuaizheng Liu
  • , Lingchen Sun
  • , Rongyuan Wu
  • , Xindong Zhang
  • , Hui Zeng
  • , Lei Zhang
  • , Tianyu Hao
  • , Lin Wang
  • , Zhe Xiao
  • , Pengzhou Ji
  • , Shu Peng Zhong
  • , Xiangming Wang
  • , Jiaqi Yan
  • , Sishun Pan
  • , Ce Wang
  • , Yibin Huang
  • Zhan Sheng Wang, Haobo Liang, Zhenghao Pan, Jinjian Wu, Yushen Zuo, Yuanbo Zhou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In this paper, we present a comprehensive overview of the NTIRE 2025 challenge on the 2nd Restore Any Image Model (RAIM) in the Wild. This challenge established a new benchmark for real-world image restoration, featuring diverse scenarios with and without reference ground truth. Participants were tasked with restoring real-captured images suffering from complex and unknown degradations, where both perceptual quality and fidelity were critically evaluated. The challenge comprised two tracks: (1) the low-light joint denoising and demosaicing (JDD) task, and (2) the image detail enhancement/-generation task. Each track included two sub-tasks. The first sub-task involved paired data with available ground truth, enabling quantitative evaluation. The second sub-task dealt with real-world yet unpaired images, emphasizing restoration efficiency and subjective quality assessed through a comprehensive user study. In total, the challenge attracted nearly 300 registrations, with 51 teams submitting more than 600 results. The top-performing methods advanced the state of the art in image restoration and received unanimous recognition from all 20+ expert judges. The datasets used in Track 1 and Track 2 are available at https://drive.google.com/drive/folders/1Mgqve-yNcE26IIieI8lMIf-25VvZRs_J and https://drive.google.com/drive/folders/1UB7nnzLwqDZOwDmD9aT8J0KVg2ag4Qae, respectively. The official challenge pages for Track 1 and Track 2 can be found at https://codalab.lisn.upsaclay.fr/competitions/21334#learn_the_details and https://codalab.lisn.upsaclay.fr/competitions/21623#learn_the_details.

Original languageEnglish
Title of host publicationProceedings - 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025
PublisherIEEE Computer Society
Pages1260-1269
Number of pages10
ISBN (Electronic)9798331599942
DOIs
Publication statusPublished - Sept 2025
Event2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025 - Nashville, United States
Duration: 11 Jun 202512 Jun 2025

Publication series

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

Conference

Conference2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025
Country/TerritoryUnited States
CityNashville
Period11/06/2512/06/25

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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