Data-driven single image deraining: A comprehensive review and new perspectives
Abstract Single Image D eraining (SID) aims at recovering the rain-free background from an
image degraded by rain streaks. For the powerful fitting ability of deep neural networks and …
image degraded by rain streaks. For the powerful fitting ability of deep neural networks and …
Generative adversarial networks: a survey on applications and challenges
MR Pavan Kumar, P Jayagopal - International Journal of Multimedia …, 2021 - Springer
Deep neural networks have attained great success in handling high dimensional data,
especially images. However, generating naturalistic images containing ginormous subjects …
especially images. However, generating naturalistic images containing ginormous subjects …
Conditional variational image deraining
Image deraining is an important yet challenging image processing task. Though
deterministic image deraining methods are developed with encouraging performance, they …
deterministic image deraining methods are developed with encouraging performance, they …
Recurrent wavelet structure-preserving residual network for single image deraining
The combination of deep learning and image prior has been widely used in single image
deraining since 2017. Recent studies have demonstrated an excellent deraining effect on …
deraining since 2017. Recent studies have demonstrated an excellent deraining effect on …
Defect attention template generation cycleGAN for weakly supervised surface defect segmentation
Surface defect segmentation is very important for the quality inspection of industrial
production and is an important pattern recognition problem. Although deep learning (DL) …
production and is an important pattern recognition problem. Although deep learning (DL) …
Rain-component-aware capsule-GAN for single image de-raining
Images taken in the rain usually have poor visual quality, which may cause difficulties for
vision-based analysis systems. The research aims to recover clean image content from a …
vision-based analysis systems. The research aims to recover clean image content from a …
Meta-learning based relation and representation learning networks for single-image deraining
Single-image deraining is a kind of computer vision task that aims to restore the image that
be degraded by rain streaks, which motivates existing methods to either directly translate the …
be degraded by rain streaks, which motivates existing methods to either directly translate the …
[HTML][HTML] Self-supervised adversarial variational learning
A natural approach for representation learning is to combine the inference mechanisms of
VAEs and the generative abilities of GANs, within a new model, namely VAEGAN. Most …
VAEs and the generative abilities of GANs, within a new model, namely VAEGAN. Most …
Progressive polarization based reflection removal via realistic training data generation
The reflection effect is unavoidable when taking photos through glasses or other transparent
materials, which introduces undesired information into pictures. Hence, removing the …
materials, which introduces undesired information into pictures. Hence, removing the …
[HTML][HTML] Contrast-Enhanced Liver Magnetic Resonance Image Synthesis Using Gradient Regularized Multi-Modal Multi-Discrimination Sparse Attention Fusion GAN
Simple Summary Contrast-enhanced MR has been used in diagnosing and treating liver
patients. Recently, development in MR-guided radiation therapy calls for daily contrast MR …
patients. Recently, development in MR-guided radiation therapy calls for daily contrast MR …