Hybrid Spectral Denoising Transformer with Guided Attention (ICCV 2023)

Hyperspectral Image Super Resolution with Real Unaligned RGB Guidance (TNNLS 2023)

PyTorch implementation of "Deep Plug-and-Play Prior for Hyperspectral Image Restoration" (Neurocomputing 2022)

A blind hyperspectral reconstruction technique termed hyperspectral demosaicing (Hy-demosaicing) exploiting spectral low-rankness and spatial correlation of hyperspectral images.

Graph and Rank Regularized Matrix Recovery for Snapshot Spectral Image Demosaicing

Model for the manuscript named "Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution" pbulished on TNNLS

PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).

Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels (CVPR, 2019) (PyTorch)

3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising (TNNLS 2020)

A collection of high-impact and state-of-the-art SR methods

pytorch implementation of Super Resolution CNN as discussed in https://personal.ie.cuhk.edu.hk/~ccloy/files/eccv_2014_deepresolution.pdf

collection of super-resolution models & algorithms

Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch

Collection of popular and reproducible image denoising works.

Blind Super-Resolution of Single Remotely Sensed Hyperspectral Image, IEEE TGSR (2023)