IIGROUP/MANIQA
[CVPRW oral 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
This tool helps you automatically assess the perceptual quality of images, mimicking how a human would rate them, without needing a perfect reference image for comparison. You input an image file, and it outputs a numerical score indicating its quality. This is ideal for professionals who need to quickly evaluate image quality at scale, such as in media production, e-commerce, or digital asset management.
411 stars. No commits in the last 6 months.
Use this if you need an automated and objective way to score image quality, especially for images that may have AI-generated distortions or other complex imperfections, without having an original, perfect version to compare against.
Not ideal if you already have a perfect reference image and want to compare the quality of a distorted version against it, as this tool is specifically designed for 'no-reference' assessment.
Stars
411
Forks
45
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 10, 2023
Commits (30d)
0
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