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MCGKT-Net: Multi-level Context Gating Knowledge Transfer Network for Single Image Deraining

19 Oct 2020

Rain streak removal in a single image is a very challenging task due to its ill-posed nature in essence.

SINGLE IMAGE DERAINING TRANSFER LEARNING

MARA-Net: Single Image Deraining Network with Multi-level connections and Adaptive Regional Attentions

29 Sep 2020

In this paper, we present a multi-level connection and adaptive regional attention network (MARA-Net) to properly restore the original background textures in rainy images.

SINGLE IMAGE DERAINING

From Rain Generation to Rain Removal

8 Aug 2020

For the single image rain removal (SIRR) task, the performance of deep learning (DL)-based methods is mainly affected by the designed deraining models and training datasets.

SINGLE IMAGE DERAINING VARIATIONAL INFERENCE

Rethinking Image Deraining via Rain Streaks and Vapors

ECCV 2020

Single image deraining regards an input image as a fusion of a background image, a transmission map, rain streaks, and atmosphere light.

IMAGE GENERATION IMAGE RESTORATION SINGLE IMAGE DERAINING

Wavelet Channel Attention Module with a Fusion Network for Single Image Deraining

17 Jul 2020

Wavelet transform and the inverse wavelet transform are substituted for down-sampling and up-sampling so feature maps from the wavelet transform and convolutions contain different frequencies and scales.

SINGLE IMAGE DERAINING

Single Image Deraining via Scale-space Invariant Attention Neural Network

9 Jun 2020

Image enhancement from degradation of rainy artifacts plays a critical role in outdoor visual computing systems.

IMAGE ENHANCEMENT SINGLE IMAGE DERAINING

Physical Model Guided Deep Image Deraining

30 Mar 2020

Single image deraining is an urgent task because the degraded rainy image makes many computer vision systems fail to work, such as video surveillance and autonomous driving.

AUTONOMOUS DRIVING SINGLE IMAGE DERAINING

Semi-DerainGAN: A New Semi-supervised Single Image Deraining Network

23 Jan 2020

Although supervised deep deraining networks have obtained impressive results on synthetic datasets, they still cannot obtain satisfactory results on real images due to weak generalization of rain removal capacity, i. e., the pre-trained models usually cannot handle new shapes and directions that may lead to over-derained/under-derained results.

SINGLE IMAGE DERAINING