Algolzw/daclip-uir
[ICLR 2024] Controlling Vision-Language Models for Universal Image Restoration. 5th place in the NTIRE 2024 Restore Any Image Model in the Wild Challenge.
This project helps anyone with degraded digital images improve their quality by removing common issues like blur, haze, noise, or poor lighting. You input an image that has a specific type of degradation, and the system outputs a clearer, restored version. This is ideal for photographers, digital archivists, graphic designers, or anyone needing to enhance visual content for better clarity or presentation.
807 stars. No commits in the last 6 months.
Use this if you have digital images suffering from common degradations like motion blur, haze, low light, or JPEG compression and need to restore them to a higher quality.
Not ideal if you're looking for advanced artistic image manipulation beyond restoration, or if your primary need is for specialized tasks like object removal or complex photo retouching.
Stars
807
Forks
51
Language
Python
License
MIT
Category
Last pushed
Aug 07, 2024
Commits (30d)
0
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