Real-world single image super-resolution: A brief review
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …
image from a low-resolution (LR) observation, has been an active research topic in the area …
Deep learning methods for solving linear inverse problems: Research directions and paradigms
The linear inverse problem is fundamental to the development of various scientific areas.
Innumerable attempts have been carried out to solve different variants of the linear inverse …
Innumerable attempts have been carried out to solve different variants of the linear inverse …
Generative diffusion prior for unified image restoration and enhancement
Existing image restoration methods mostly leverage the posterior distribution of natural
images. However, they often assume known degradation and also require supervised …
images. However, they often assume known degradation and also require supervised …
Image-to-image translation: Methods and applications
Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …
domain while preserving the content representations. I2I has drawn increasing attention and …
Blind image super-resolution: A survey and beyond
Blind image super-resolution (SR), aiming to super-resolve low-resolution images with
unknown degradation, has attracted increasing attention due to its significance in promoting …
unknown degradation, has attracted increasing attention due to its significance in promoting …
CVANet: Cascaded visual attention network for single image super-resolution
Deep convolutional neural networks (DCNNs) have exhibited excellent feature extraction
and detail reconstruction capabilities for single image super-resolution (SISR) …
and detail reconstruction capabilities for single image super-resolution (SISR) …
High-resolution image inpainting using multi-scale neural patch synthesis
Recent advances in deep learning have shown exciting promise in filling large holes in
natural images with semantically plausible and context aware details, impacting …
natural images with semantically plausible and context aware details, impacting …
Generative adversarial networks for image super-resolution: A survey
Single image super-resolution (SISR) has played an important role in the field of image
processing. Recent generative adversarial networks (GANs) can achieve excellent results …
processing. Recent generative adversarial networks (GANs) can achieve excellent results …
Denoising the optical fiber seismic data by using convolutional adversarial network based on loss balance
X Dong, Y Li - IEEE Transactions on Geoscience and Remote …, 2020 - ieeexplore.ieee.org
Distributed optical fiber acoustic sensing (DAS) is a new and rapid-developing detection
technology in seismic exploration. Unfortunately, due to the weak energy of scattered optical …
technology in seismic exploration. Unfortunately, due to the weak energy of scattered optical …
Human guided ground-truth generation for realistic image super-resolution
How to generate the ground-truth (GT) image is a critical issue for training realistic image
super-resolution (Real-ISR) models. Existing methods mostly take a set of high-resolution …
super-resolution (Real-ISR) models. Existing methods mostly take a set of high-resolution …