Expanding training data diversity, adopting two-stage optimization, and applying geometric self-ensemble raises Restormer performance on Gaussian color denoising at sigma=50 by 3.366 dB PSNR on the NTIRE 2026 validation set.
Practical blind image denoising via Swin- Conv-UNet and data synthesis.Machine Intelligence Re- search, 20(6):822–836, 2023
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Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoising
Expanding training data diversity, adopting two-stage optimization, and applying geometric self-ensemble raises Restormer performance on Gaussian color denoising at sigma=50 by 3.366 dB PSNR on the NTIRE 2026 validation set.