Another round of Reddit's r/TheWayWeWere colorizations using my latest unreleased DeOldify model. Yay!pic.twitter.com/w6bzFrFHHF
Obsessively pursuing the perfection of image and video colorization/restoration using deep learning. Creator of DeOldify.
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Another round of Reddit's r/TheWayWeWere colorizations using my latest unreleased DeOldify model. Yay!pic.twitter.com/w6bzFrFHHF
Image sources: https://www.reddit.com/r/TheWayWeWere/comments/eyvs6c/jewish_couple_from_sarajevo_austrohungaria_by/ … https://www.reddit.com/r/TheWayWeWere/comments/ez87zt/woman_purchasing_berries_at_a_grocery_stand_in/ … https://www.reddit.com/r/TheWayWeWere/comments/eziv4c/june_1941_wife_of_defense_worker_washing_clothes/ …https://www.reddit.com/r/TheWayWeWere/comments/ezf022/company_lunch_at_crespi_cotton_mill_capriate_san/ …
Jason, big fan of your work (like most of the world!). Do you think there is the possibility to add some 'context awareness' to deoldify.. As in if one can define a condition, say 'celebration' then the generated image should have more colour, as opposed to say 'general'..
That's already part of the architecture, I'd argue. That's basically what a neural network excels at, especially with attention. It's just that it needs "more model" basically (more parameters, more data, etc) in order to be better at this sort of thing, I think.
To be clear, I'm saying that the "condition" you're talking about should be derived from the image by the model itself.
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