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Image super-resolution: A comprehensive review, recent trends, challenges and applications
Super resolution (SR) is an eminent system in the field of computer vison and image
processing to improve the visual perception of the poor-quality images. The key objective of …
processing to improve the visual perception of the poor-quality images. The key objective of …
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 …
Promptir: Prompting for all-in-one image restoration
Image restoration involves recovering a high-quality clean image from its degraded version.
Deep learning-based methods have significantly improved image restoration performance …
Deep learning-based methods have significantly improved image restoration performance …
Swinir: Image restoration using swin transformer
Image restoration is a long-standing low-level vision problem that aims to restore high-
quality images from low-quality images (eg, downscaled, noisy and compressed images) …
quality images from low-quality images (eg, downscaled, noisy and compressed images) …
Swin2sr: Swinv2 transformer for compressed image super-resolution and restoration
Compression plays an important role on the efficient transmission and storage of images
and videos through band-limited systems such as streaming services, virtual reality or …
and videos through band-limited systems such as streaming services, virtual reality or …
Learning continuous image representation with local implicit image function
How to represent an image? While the visual world is presented in a continuous manner,
machines store and see the images in a discrete way with 2D arrays of pixels. In this paper …
machines store and see the images in a discrete way with 2D arrays of pixels. In this paper …