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NTIRE 2026 challenge advances reflection removal with new dataset

By PulseAugur Editorial · [1 sources] ·

The NTIRE 2026 challenge focused on single-image reflection removal (SIRR) in the wild, addressing a gap in real-world applications. A new dataset, OpenRR-5k, was introduced to test methods on diverse real-world reflection scenarios. The challenge saw significant participation, with top-performing methods advancing the state-of-the-art in reflection removal and receiving expert validation. AI

IMPACT Advances image restoration techniques, potentially improving visual quality in applications using real-world imagery.

RANK_REASON The cluster reports on a research challenge and dataset release. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

NTIRE 2026 challenge advances reflection removal with new dataset

COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Jie Cai, Kangning Yang, Zhiyuan Li, Florin-Alexandru Vasluianu, Radu Timofte, Jinlong Li, Jinglin Shen, Zibo Meng, Junyan Cao, Lu Zhao, Pengwei Liu, Yuyi Zhang, Fengjun Guo, Jiagao Hu, Zepeng Wang, Fei Wang, Daiguo Zhou, Yi'ang Chen, Honghui Zhu, Mengru … ·

    NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods

    arXiv:2604.10321v3 Announce Type: replace Abstract: 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 syntheti…

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