NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods
In this paper, we review the NTIRE 2026 challenge on single-image reflection removal (SIRR) in the wild. SIRR is a fundamental task in image restoration. Despite progress in academic research, most methods are tested on synthetic images or limited real-world images, creating a gap in real-world applications. In this challenge, we provide participants with the OpenRR-5k dataset. This dataset requires participants to process real-world images covering a range of reflection scenarios and intensities, aiming to generate clean images without reflections. The challenge attracted more than 100 registrations, with eleven of them participating in the final testing phase. The top-ranked methods adv...
| Authors | Jie Cai, Kangning Yang, Zhiyuan Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 11 April 2026 |
| Last updated at source | 4 August 2026 |
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- qiuzhangTiTi/OpenRR-5kDataset · cited by
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- qiuzhangTiTi/OpenRR-5kDataset
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