IVCVJun 2, 2025

NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution

arXiv:2506.02197v227 citationsh-index: 982025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Originality Synthesis-oriented
AI Analysis

This addresses the problem of improving RAW image processing for photography and imaging applications, but it is incremental as it focuses on benchmarking existing methods rather than introducing new ones.

The paper reviews the NTIRE 2025 challenge on RAW image restoration and super-resolution, tackling the problem of restoring and upscaling RAW images with degradations like blur and noise, and reports that 45 participants submitted results, presenting the current state-of-the-art in this area.

This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. The goal of this challenge is two fold, (i) restore RAW images with blur and noise degradations, (ii) upscale RAW Bayer images by 2x, considering unknown noise and blur. In the challenge, a total of 230 participants registered, and 45 submitted results during thee challenge period. This report presents the current state-of-the-art in RAW Restoration.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes