jiaxi-jiang/FBCNN
Official Code for ICCV 2021 paper "Towards Flexible Blind JPEG Artifacts Removal (FBCNN)"
This tool helps photographers, graphic designers, and social media managers improve the visual quality of their images. It takes a JPEG image, which may show blocky or blurry artifacts from compression, and produces a cleaner, higher-quality version. It's designed for anyone needing to clean up visual imperfections in compressed images.
512 stars. No commits in the last 6 months.
Use this if you have JPEG images, whether single or double compressed, that show noticeable compression artifacts and you need to restore their visual quality for better presentation.
Not ideal if your images are already high-quality and uncompressed, or if you need to perform more advanced image editing like object removal or color grading.
Stars
512
Forks
50
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 19, 2024
Commits (30d)
0
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