Video super-resolution (VSR) aims to restore a photo-realistic high-resolution (HR) video
frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple …

Structures matter in single image super resolution (SISR). Recent studies benefiting from
generative adversarial network (GAN) have promoted the development of SISR by …

Deep neural networks with a massive number of layers have made a remarkable
breakthrough on single image super-resolution (SR), but sacrifice computation complexity …

Recent studies have shown that deep networks can achieve promising results for image
denoising. However, how to simultaneously incorporate the valuable achievements of …

Training a single deep blind model to handle different quality factors for JPEG image
artifacts removal has been attracting considerable attention due to its convenience for …

Abstract Space-time video super-resolution (STVSR) aims to increase the spatial and
temporal resolutions of low-resolution and low-frame-rate videos. Recently, deformable …

Deep learning has made unprecedented progress in image restoration (IR), where residual
block (RB) is popularly used and has a significant effect on promising performance …

Structures matter in single image super-resolution (SISR). Benefiting from generative
adversarial networks (GANs), recent studies have promoted the development of SISR by …

Interactive image restoration aims to restore images by adjusting several controlling
coefficients, which determine the restoration strength. Existing methods are restricted in …

Controllable image denoising aims to generate clean samples with human perceptual priors
and balance sharpness and smoothness. In traditional filter-based denoising methods, this …