Transweather: Transformer-based restoration of images degraded by adverse weather conditions
JMJ Valanarasu, R Yasarla… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Removing adverse weather conditions like rain, fog, and snow from images is an important
problem in many applications. Most methods proposed in the literature have been designed …
problem in many applications. Most methods proposed in the literature have been designed …
Restoring images in adverse weather conditions via histogram transformer
Transformer-based image restoration methods in adverse weather have achieved significant
progress. Most of them use self-attention along the channel dimension or within spatially …
progress. Most of them use self-attention along the channel dimension or within spatially …
Deep dense multi-scale network for snow removal using semantic and depth priors
Images captured in snowy days suffer from noticeable degradation of scene visibility, which
degenerates the performance of current vision-based intelligent systems. Removing snow …
degenerates the performance of current vision-based intelligent systems. Removing snow …
Perception Methods for Adverse Weather Based on Vehicle Infrastructure Cooperation System: A Review
Environment perception plays a crucial role in autonomous driving technology. However,
various factors such as adverse weather conditions and limitations in sensing equipment …
various factors such as adverse weather conditions and limitations in sensing equipment …
A survey of deep learning-based image restoration methods for enhancing situational awareness at disaster sites: the cases of rain, snow and haze
This survey article is concerned with the emergence of vision augmentation AI tools for
enhancing the situational awareness of first responders (FRs) in rescue operations. More …
enhancing the situational awareness of first responders (FRs) in rescue operations. More …
Gridformer: Residual dense transformer with grid structure for image restoration in adverse weather conditions
Image restoration in adverse weather conditions is a difficult task in computer vision. In this
paper, we propose a novel transformer-based framework called GridFormer which serves as …
paper, we propose a novel transformer-based framework called GridFormer which serves as …
Image desnowing via deep invertible separation
Images taken on snowy days often suffer from severe negative visual effects caused by
snowflakes. The task of removing snowflakes from a snowy image is known as image …
snowflakes. The task of removing snowflakes from a snowy image is known as image …
Task-driven deep image enhancement network for autonomous driving in bad weather
Visual perception in autonomous driving is a crucial part of a vehicle to navigate safely and
sustainably in different traffic conditions. However, in bad weather such as heavy rain and …
sustainably in different traffic conditions. However, in bad weather such as heavy rain and …
Lightweight image de-snowing: A better trade-off between network capacity and performance
Z Chen, Y Sun, X Bi, J Yue - Neural Networks, 2023 - Elsevier
The single image de-snowing task is an essential topic in computer vision, as images
captured on snowy days degrade the performance of current vision-based intelligent …
captured on snowy days degrade the performance of current vision-based intelligent …
Reconstructing Snow-Free Sentinel-2 Satellite Imagery: A Generative Adversarial Network (GAN) Approach
Sentinel-2 satellites are one of the major instruments in remote sensing (RS) technology that
has revolutionized Earth observation research, as its main goal is to offer high-resolution …
has revolutionized Earth observation research, as its main goal is to offer high-resolution …