The Third Challenge on Image Denoising at NTIRE 2026: Methods and Results
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Abstract (arXiv)
This paper reports on the NTIRE 2026 Challenge on Image Denoising, specifically focusing on the high-noise regime (σ = 50). The competition investigates advanced neural architectures designed to restore high-fidelity details from images corrupted by additive white Gaussian noise (AWGN). Unlike constrained benchmarks, this track emphasizes peak quantitative performance, measured by Peak Signal-to-Noise Ratio (PSNR), without limitations on parameter count or computational overhead. By synthesizing contributions from 20 finalist teams out of 116 registrants, this report benchmarks the latest technical innovations and provides a comprehensive snapshot of the current state-of-the-art in unconstrained image restoration.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 44 of its 66 references that are in the map. First posted on arXiv 14 Jun 2026.
Builds on
44 of 66 references.
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32 more
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