Single Image Dehazing

37 papers with code • 2 benchmarks • 7 datasets

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Most implemented papers

Generic Model-Agnostic Convolutional Neural Network for Single Image Dehazing

Seanforfun/GMAN_Net_Haze_Removal 5 Oct 2018

Haze and smog are among the most common environmental factors impacting image quality and, therefore, image analysis.

Contrastive Learning for Compact Single Image Dehazing

GlassyWu/AECR-Net CVPR 2021

In this paper, we propose a novel contrastive regularization (CR) built upon contrastive learning to exploit both the information of hazy images and clear images as negative and positive samples, respectively.

Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing

engindeniz/Cycle-Dehaze 14 May 2018

In this paper, we present an end-to-end network, called Cycle-Dehaze, for single image dehazing problem, which does not require pairs of hazy and corresponding ground truth images for training.

FFA-Net: Feature Fusion Attention Network for Single Image Dehazing

zhilin007/FFA-Net 18 Nov 2019

The FFA-Net architecture consists of three key components: 1) A novel Feature Attention (FA) module combines Channel Attention with Pixel Attention mechanism, considering that different channel-wise features contain totally different weighted information and haze distribution is uneven on the different image pixels.

Benchmarking Single Image Dehazing and Beyond

inyong37/Vision 12 Dec 2017

We present a comprehensive study and evaluation of existing single image dehazing algorithms, using a new large-scale benchmark consisting of both synthetic and real-world hazy images, called REalistic Single Image DEhazing (RESIDE).

Single Image Dehazing Using Color Ellipsoid Prior

mtbui2010/CEP IEEE Transactions on Image Processing 2018

The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry.

Densely Connected Pyramid Dehazing Network

hezhangsprinter/DCPDN CVPR 2018

We propose a new end-to-end single image dehazing method, called Densely Connected Pyramid Dehazing Network (DCPDN), which can jointly learn the transmission map, atmospheric light and dehazing all together.

PAD-Net: A Perception-Aided Single Image Dehazing Network

guanlongzhao/single-image-dehazing 8 May 2018

In this work, we investigate the possibility of replacing the $\ell_2$ loss with perceptually derived loss functions (SSIM, MS-SSIM, etc.)

Deep-Energy: Unsupervised Training of Deep Neural Networks

AlonaGolts/Deep_Energy 31 May 2018

The success of deep learning has been due, in no small part, to the availability of large annotated datasets.