yuanzhi-zhu/DiffPIR
"Denoising Diffusion Models for Plug-and-Play Image Restoration", Yuanzhi Zhu, Kai Zhang, Jingyun Liang, Jiezhang Cao, Bihan Wen, Radu Timofte, Luc Van Gool.
This project helps image specialists, graphic designers, or anyone working with visual media to significantly improve the quality of degraded images. It takes blurry, low-resolution, or incomplete images and outputs sharper, higher-resolution, and restored versions. This tool is for professionals who need to salvage or enhance images for publication, analysis, or presentation.
495 stars. No commits in the last 6 months.
Use this if you need to restore or enhance images that suffer from blur, low resolution, or missing parts, achieving both high fidelity and natural visual quality.
Not ideal if you require extremely fast processing for real-time applications or have very limited computational resources, as it can involve multiple processing steps.
Stars
495
Forks
46
Language
Python
License
MIT
Category
Last pushed
Nov 27, 2024
Commits (30d)
0
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