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Greatest papers with code

Attentive Generative Adversarial Network for Raindrop Removal from a Single Image

CVPR 2018 rui1996/DeRaindrop

This injection of visual attention to both generative and discriminative networks is the main contribution of this paper.

RAIN REMOVAL

Multi-Stage Progressive Image Restoration

4 Feb 2021swz30/MPRNet

At each stage, we introduce a novel per-pixel adaptive design that leverages in-situ supervised attention to reweight the local features.

DEBLURRING IMAGE DENOISING IMAGE RESTORATION SINGLE IMAGE DERAINING

Image De-raining Using a Conditional Generative Adversarial Network

21 Jan 2017hezhangsprinter/ID-CGAN

Hence, it is important to solve the problem of single image de-raining/de-snowing.

RAIN REMOVAL

A Survey on Rain Removal from Video and Single Image

18 Sep 2019hongwang01/Video-and-Single-Image-Deraining

The investigations on rain removal from video or a single image has thus been attracting much research attention in the field of computer vision and pattern recognition, and various methods have been proposed against this task in the recent years.

4 RAIN REMOVAL

Progressive Image Deraining Networks: A Better and Simpler Baseline

CVPR 2019 csdwren/PReNet

To handle this issue, this paper provides a better and simpler baseline deraining network by considering network architecture, input and output, and loss functions.

SINGLE IMAGE DERAINING SSIM

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset

CVPR 2019 stevewongv/SPANet

First, we propose a semi-automatic method that incorporates temporal priors and human supervision to generate a high-quality clean image from each input sequence of real rain images.

SINGLE IMAGE DERAINING

Gated Context Aggregation Network for Image Dehazing and Deraining

21 Nov 2018cddlyf/GCANet

Image dehazing aims to recover the uncorrupted content from a hazy image.

IMAGE DEHAZING RAIN REMOVAL

Single Image Deraining: A Comprehensive Benchmark Analysis

CVPR 2019 lsy17096535/Single-Image-Deraining

We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy images. This dataset highlights diverse data sources and image contents, and is divided into three subsets (rain streak, rain drop, rain and mist), each serving different training or evaluation purposes.

SINGLE IMAGE DERAINING

Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning

CVPR 2019 liruoteng/HeavyRainRemoval

This filtering is guided by a rain-free residue image --- its content is used to set the passbands for the two channels in a spatially-variant manner so that the background details do not get mixed up with the rain-streaks.

IMAGE RESTORATION RAIN REMOVAL

Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning

10 Apr 2019liruoteng/HeavyRainRemoval

This filtering is guided by a rain-free residue image --- its content is used to set the passbands for the two channels in a spatially-variant manner so that the background details do not get mixed up with the rain-streaks.

IMAGE RESTORATION RAIN REMOVAL