NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 34 of its 50 references that are in the map. First posted on arXiv 2 Jun 2025.
Builds on
34 of 50 references.
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22 more
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Citing papers per year: 2025: 3; 2026: 2.
5 papers.
- 2025NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfacescited by 3
- 2026How far have we gone in Generative Image Restoration? A study on its capability, limitations and evaluation practicescited by 2
- 2025NTIRE 2025 Image Shadow Removal Challenge Reportcited by 1
- 2025NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Resultscited by 1
- 2026HarnessIR: Harnessing Multimodal Foundation Models for Universal Real-World Image Restorationcited by 0
- 2026HarnessIR: Harnessing Multimodal Foundation Models for Universal Real-World Image Restoration7 Oct 2026
- 2026How far have we gone in Generative Image Restoration? A study on its capability, limitations and evaluation practices5 Mar 2026
- 2025NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Results15 Oct 2025
- 2025NTIRE 2025 Image Shadow Removal Challenge Report18 Jun 2025
- 2025NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces6 Jun 2025