From Scratch Implementation of ResShift Paper for Image Super-Resolution

🚧 Blog Post Coming Soon

This blog post will dive deep into my complete from-scratch implementation of the ResShift paper for image super-resolution. I'll explain how I built an efficient diffusion-based super-resolution model using a U-Net architecture with Swin Transformer blocks, including the residual shifting mechanism that reduces diffusion steps to just 15 timesteps. The post will cover architecture design, training on DIV2K dataset, and lessons learned from implementing this state-of-the-art approach to image enhancement.

Check out the implementation: GitHub Repository

Stay tuned for detailed explanations, code walkthroughs, and practical insights!