KAIR
Explore an extensive collection of training and testing codes for leading image restoration models, including USRNet, DnCNN, FFDNet, SRMD, DPSR, MSRResNet, ESRGAN, BSRGAN, SwinIR, VRT, and RVRT. This repository offers capabilities for image enhancement tasks such as super-resolution, deblurring, and denoising leveraging diffusion models and deep learning frameworks. Stay informed with continuous updates and interactive demonstrations, and investigate the application of these methods in practical scenarios via differentiable programming interfaces. It serves as a valuable resource for researchers and developers in the field of visual computing.
