computer-vision-10

Low-light Image Deblurring and Enhancement

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

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LOL-Blur

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LOL-Blur

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Most implemented papers

Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement

Radu Timofte, Haoqian Wang, Jing Lin, Yulun Zhang, Hao Bian•Sat Mar 11 2023

A simple yet principled One-stage Retinex-based Framework (ORF), designed an Illumination-Guided Transformer (IGT) that utilizes illumination representations to direct the modeling of non-local interactions of regions with different lighting conditions, and obtains the algorithm, Retinexformer.

493

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LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

Chen Change Loy, Shangchen Zhou, Chongyi Li•Sun Feb 06 2022

This work introduces a novel data synthesis pipeline that models realistic low-light blurring degradations and presents the first large-scale dataset, LOL-Blur, and an effective network, named LEDNet, to perform joint low-light enhancement and deblurring.

191 0

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You Only Need One Color Space: An Efficient Network for Low-light Image Enhancement

Qingsen Yan, Peng Wu, Yixu Feng, Cheng Zhang, Pei Wang, Yanning Zhang•Wed Feb 07 2024

A novel trainable color space, named Horizontal/Vertical-Intensity (HVI), which not only decouples brightness and color from RGB channels to mitigate the instability during enhancement but also adapts to low-light images in different illumination ranges due to the trainable parameters.

60 0

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