DocDiff
ACM Multimedia 2023: DocDiff: Document Enhancement via Residual Diffusion Models. Also contains 1597 red seals in Chinese scenes, along with their corresponding binary masks.
Enhance documents by reducing blur, noise, and other imperfections using a specialized AI model.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeACM Multimedia 2023: DocDiff: Document Enhancement via Residual Diffusion Models. Also contains 1597 red seals in Chinese scenes, along with their corresponding binary masks.
DocDiff has 349 stars on GitHub. It has been forked 33 times. DocDiff is written mainly in Python. It has been in active development since 2023. DocDiff is available under the MIT license. Its main topics are dataset, deblurring, deep-learning, diffusion-models.
What is DocDiff?
ACM Multimedia 2023: DocDiff: Document Enhancement via Residual Diffusion Models. Also contains 1597 red seals in Chinese scenes, along with their corresponding binary masks.
Is DocDiff open source?
DocDiff is an open-source project. It is released under the MIT license.
Is DocDiff free?
Yes. DocDiff is free and open source — you can use, modify and self-host it.
What license does DocDiff use?
DocDiff is available under the MIT license.
What language is DocDiff written in?
DocDiff is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/royalvice-docdiff.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.