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Also if you have multiple pixelated/blurry images that helps you can reconstruct it more easily, e.g. if different newspapers print pixelated picture of the "su
by zerd 6y ago
Also if you have multiple pixelated/blurry images that helps you can reconstruct it more easily, e.g. if different newspapers print pixelated picture of the "suspect" you can reconstruct it pretty accurately.
Machine learning can also do a surprising good job of it, especially if you know what the target is (e.g. a face) https://www.vox.com/future-perfect/2019/9/4/20848008/ai-machine-learning-enhance-button https://www.vox.com/future-perfect/2019/9/4/20848008/ai-mach...
Sample code: https://gist.github.com/JonathanFly/80b669a72bf624d17b56a1cfec742588#file-progressivefacesuperresolutiondemo-ipynb https://gist.github.com/JonathanFly/80b669a72bf624d17b56a1cf...
- eru 6y ago> Machine learning can also do a surprising good job of it, especially if you know what the target is (e.g. a face) Yes. Though that's just a corollary of doing better when you know something about the probability distribution of inputs. (But a very useful and practical corollary. My formulation didn't give any hint how you might make use of that knowledge of the distribution.)