When photographing a light source with a smartphone camera, light smudging often occurs. Our model contributes to improving the image quality degraded by the spread of light around the light source.

pytorch implementation of IKP

torch implementation of IKC

IKC: Blind Super-Resolution With Iterative Kernel Correction

Official implementation of "Pixel-level Kernel Estimation for Blind Super-Resolution", IEEE Access 2021.

A pytorch implementation of Learning Detail-Structure Alternative Optimization for Blind Super-Resolution.

Blind Super Resolution based on USRNet and Kernel GAN

This project is the official implementation of 'Meta-Learning based Degradation Representation for Blind Super-Resolution', TIP2023

Open source image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art deep learning models. Also acts as the companion code for the MDPI Sensors journal paper titled 'The Best of Both Worlds: A Framework for Combining Degradation Prediction with High Performance Super-Resolution Networks'

Official PyTorch implementation of the paper "Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images", IEEE Transactions on Instrumentation and Measurement (TIM) 2024. CSBSR is an advanced version of our previous work CSSR [MVA'21].

Official PyTorch Implementation of "StarSRGAN: Improving Real-World Blind Super-Resolution" (WSCG 2023)

Asymmetric CNN for image super-resolution (IEEE Transactions on Systmes, Man, and Cybernetics: Systems 2021)

This project is the official implementation of 'Knowledge Distillation based Degradation Estimation for Blind Super-Resolution', ICLR2023

Official PyTorch code for Flow-based Kernel Prior with Application to Blind Super-Resolution (FKP, CVPR2021)

Official PyTorch implementation of the paper "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.