高斯噪声下图像去噪新突破，20支团队挑战极限性能。
The Third Challenge on Image Denoising at NTIRE 2026: Methods and Results
- 采用无限制神经架构，在σ=50噪声下追求最高清晰度。
- 20支决赛队贡献方案，实现当前最先进去噪效果。
- 适合关注图像恢复前沿的开发者与研究者。
本文报告了NTIRE 2026图像去噪挑战赛，聚焦于高噪声场景（σ=50）。竞赛针对加性白高斯噪声（AWGN）污染的图像，设计先进神经架构以恢复高保真细节。不同于受限基准测试，本赛道强调峰值定量性能，以峰值信噪比（PSNR）为唯一指标，不限制参数量或计算开销。通过整合116名参赛者中脱颖而出的20支决赛团队的成果，本报告系统评估了最新的技术突破，为无约束图像恢复的当前最先进技术提供了全面快照。
原文摘要 · Abstract (English)
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.
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