Finally all the CSI and detective shows are believable again: ENHANCE!!!
Surprisingly there's a daguerreotype of John Quincy Adams from 1843[1], the AI could use that; perhaps "enhance" the time backwards a bit, to make him 15 years younger.
[1]: https://en.m.wikipedia.org/wiki/File:John_Quincy_Adams_-_cop...
What happens if it's only 80% sure? Do you get a high-res John Quincy Adams or an admission that it can't identify the image content? If I feed it a low-res picture of Michael Faraday or Henry Clay, will I receive the finely sculpted jowls of John Quincy Adams in return?
https://www.theverge.com/2023/3/13/23637401/samsung-fake-moo...
But I also had a similar thought. Use a combination of an image search engine like TinEye, and something like ClearviewAI, to actually either find a larger image of the submitted photo, or of more photos of the person in question, and reconstruct what they look like based on all of that additional data.
E.g. if I send a photo of an olympic podium where winners are pixelated and ask the AI to enhance, I'd like it to use other elements of the pixelated photo to recognize the olympic event and year, search some other database to find the winners and enhance the photo so that the people on the podium were those who actually stood on that podium.
Tangent to that: does anyone know if there are any free-to-use tools (or open-source models) for doing video-based image super-resolution?
(I imagine that such a tool could take video files directly; but that the actual underlying model would likely require that you first convert your video into an image containing a grid of sampled frames, making it essentially an image2image model that learns to sample from reference images. A bit like the image2image models trained to output depth maps given stereo-camera photo pairs.)