GFPGAN has several potential use cases. Firstly, it can be used in the field of image restoration to restore old photos and enhance the quality of deteriorated images. This could be particularly useful for archivists, historians, and photographers who often work with old photographs and need to preserve their historical or sentimental value. Secondly, GFPGAN can be employed in the creation of AI-generated faces and characters, used in video games, movies, or virtual reality environments. By generating high-quality and realistic faces, GFPGAN has the potential to save time and resources for artists and developers who would otherwise have to manually create or capture these faces. Furthermore, GFPGAN has the potential to be integrated into various software applications, such as photo editing tools or social media platforms, to provide users with advanced face restoration capabilities and improve the quality of their photos. Overall, GFPGAN's ability to restore old photos and generate AI faces opens up possibilities for practical applications and product development in the fields of image restoration, entertainment, and software integration.
- Cost per run
- Avg run time
- Nvidia T4 GPU
You can use this area to play around with demo applications that incorporate the Gfpgan model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.
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Summary of this model and related resources.
Practical face restoration algorithm for *old photos* or *AI-generated face...Read more »
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|Cost per Run
|Nvidia T4 GPU
|Average Completion Time