NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge
- URL: http://arxiv.org/abs/2506.01394v1
- Date: Mon, 02 Jun 2025 07:43:35 GMT
- Title: NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge
- Authors: Jie Liang, Radu Timofte, Qiaosi Yi, Zhengqiang Zhang, Shuaizheng Liu, Lingchen Sun, Rongyuan Wu, Xindong Zhang, Hui Zeng, Lei Zhang,
- Abstract summary: The NTIRE 2025 challenge established a new benchmark for real-world image restoration.<n>The challenge attracted nearly 300 registrations, with 51 teams submitting more than 600 results.<n>The top-performing methods advanced the state of the art in image restoration and received unanimous recognition from all 20+ expert judges.
- Score: 60.38046597325693
- License: http://creativecommons.org/licenses/by-sa/4.0/
- 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.
Related papers
- NTIRE 2025 Image Shadow Removal Challenge Report [125.80015208285496]
This work examines the findings of the NTIRE 2025 Shadow Removal Challenge.<n>A total of 306 participants have registered, with 17 teams successfully submitting their solutions.<n>The challenge had two evaluation tracks: one focusing on reconstruction fidelity and the other on visual perception through a user study.
arXiv Detail & Related papers (2025-06-18T14:58:49Z) - NTIRE 2025 Challenge on Image Super-Resolution ($\times$4): Methods and Results [159.15538432295656]
The NTIRE 2025 image super-resolution ($times$4) challenge is one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025.<n>The challenge aims to recover high-resolution (HR) images from low-resolution (LR) counterparts generated through bicubic downsampling with a $times$4 scaling factor.<n>A total of 286 participants registered for the competition, with 25 teams submitting valid entries.
arXiv Detail & Related papers (2025-04-20T12:08:22Z) - NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge [60.21380105535203]
The RAIM challenge constructed a benchmark for image restoration in the wild.
The participants were required to restore the real-captured images from complex and unknown degradation.
Top-ranked methods improved the state-of-the-art restoration performance and obtained unanimous recognition from all 18 judges.
arXiv Detail & Related papers (2024-05-16T09:26:13Z) - NTIRE 2021 Challenge on Image Deblurring [111.14036064783835]
We describe the challenge specifics and the evaluation results from the 2 competition tracks with the proposed solutions.
In each competition, there were 338 and 238 registered participants and in the final testing phase, 18 and 17 teams competed.
The winning methods demonstrate the state-of-the-art performance on the image deblurring task with the jointly combined artifacts.
arXiv Detail & Related papers (2021-04-30T09:12:53Z) - NTIRE 2020 Challenge on Image Demoireing: Methods and Results [111.72904895149804]
The challenge was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020.
The methods were ranked in terms of their fidelity, measured using the peak signal-to-noise ratio (PSNR) between the ground truth clean images and the restored images produced by the participants' methods.
arXiv Detail & Related papers (2020-05-06T22:05:58Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.