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20182024
most citedRethinking Image Deraining via Rain Streaks and Vapors

6 citations · 17 across the 8 of their papers we have counts for

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9 papers · 1 filter

cs.CV20243 cited

CasDyF-Net: Image Dehazing via Cascaded Dynamic Filters

Wang Yinglong, He Bin

Image dehazing aims to restore image clarity and visual quality by reducing atmospheric scattering and absorption effects. While deep learning has made significant strides in this…

cs.CV2023

Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Network

Yinglong Wang, Zhen Liu, Jianzhuang Liu +2

This paper presents a novel network structure with illumination-aware gamma correction and complete image modelling to solve the low-light image enhancement problem. Low-light envi…

cs.CV20206 cited

Rethinking Image Deraining via Rain Streaks and Vapors

Yinglong Wang, Yibing Song, Chao Ma +1

Single image deraining regards an input image as a fusion of a background image, a transmission map, rain streaks, and atmosphere light. While advanced models are proposed for imag…

cs.CV2019

Deep Image Deraining Via Intrinsic Rainy Image Priors and Multi-scale Auxiliary Decoding

Yinglong Wang, Chao Ma, Bing Zeng

Different rain models and novel network structures have been proposed to remove rain streaks from single rainy images. In this work, we bring attention to the intrinsic priors and…

cs.CV20194 cited

Gradient Information Guided Deraining with A Novel Network and Adversarial Training

Yinglong Wang, Haokui Zhang, Yu Liu +2

In recent years, deep learning based methods have made significant progress in rain-removing. However, the existing methods usually do not have good generalization ability, which l…

cs.CV2019

Deep Single Image Deraining Via Estimating Transmission and Atmospheric Light in rainy Scenes

Yinglong Wang, Qinfeng Shi, Ehsan Abbasnejad +3

Rain removal in images/videos is still an important task in computer vision field and attracting attentions of more and more people. Traditional methods always utilize some incompl…