arXiv:2506.02197
NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
Deep Learning-Driven Ultra-High-Definition Image Restoration: A Survey
Trustworthy Image Super-Resolution via Generative Pseudoinverse
VibrantLeaves: A principled parametric image generator for training deep restoration models
Exploring Diffusion with Test-Time Training on Efficient Image Restoration
토론
이 논문과 연결된 포럼 글이 아직 없습니다.