A simple and complete implementation of super-resolution paper.

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C , C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version ongoing

Replacing Mamba with xLSTM! It works better. We show that xLSTM-Unet can be an effective semantic segmentation backbone.

Approaching (Almost) Any Machine Learning Problem

Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022