Re-parameterized Multi-scale Fusion Network for Efficient Extreme Low-light Raw Denoising

Re-parameterized Multi-scale Fusion Network for Efficient Extreme Low-light Raw Denoising

Practical low-light denoising/enhancement solutions often require fast computation,high memory efficiency,and can achieve visually high-quality restoration results.Most existing methods aim to restore quality but compromise on speed and memory requirements,which limits their usefulness to a large ex...

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Bibliographic Details
Main Author: WEI Kai-xuan, FU Ying
Format: Article
Language:zho
Published: Editorial office of Computer Science 2022-08-01
Series:Jisuanji kexue
Subjects:
re-parameterization convolutional unit|multi-scale fusion|spatial-channel parallel attention module|extreme low-light denoising
Online Access:https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-8-120.pdf

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