Image-Super-Resolution-via-Iterative-Refinement
Image-Super-Resolution-via-Iterative-Refinement copied to clipboard
Janspiry
Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
Hello, [MSU Graphics & Media Lab Video Group](https://videoprocessing.ai/) has recently launched two new Super-Resolution Benchmarks. * [Video Upscalers Benchmark: Quality Enhancement](https://videoprocessing.ai/benchmarks/video-upscalers.html) determines the best upscaling methods for increasing video resolution...
 
Thank you for your contribution. I am using your code to perform some conditional generation tasks, not super-resolution tasks. The difficulty I encountered was that the generated image had a...
Thank you very much for the author's magnificent work~ I am just beginning to understand the work of diffusion models in superresolution. I would like to ask, does a diffusion...
https://github.com/Janspiry/Image-Super-Resolution-via-Iterative-Refinement/blob/01d27a7cbfa8502be1d8dbd4ee02fcbd5e44389d/model/ddpm_modules/diffusion.py#L218 In this line it requires the input shape be same as the output shape in conditional image generation that is not true. Instead of that, the output shape from...
How can this code be changed to conditional generation? I changed whether LR is required in the train to LRHR, and the result is an error, can this LRHR only...
Hi, thank you for sharing this work! When I tried to run the Test/Evaluation code, I found there was a small error in your code(Probably?) In the val.py's col 23...
hello,when i read your code (sr.py)，I have a doubt that you train the network and saves the network after validation, but in the test phase, it doesn't load the trained...
What is the minimum resource requirement for this project? This project can be run via NVIDIA GTX 1080 or higher?
How do we perform distributed training in this project? or how to modify the code for distributed training? Thank you very much!!!
