Not really,
I'm in my sixties, and it's surprisingly difficult to get round the biases these models have of young, perfect people, if you want to get images of older people.
Try the single word prompt 'woman' and see what you get...
Have larger diffusion models gotten to synthetic training dogfooding yet?
The irony is that once we get there, we can address biases in historical data. I.e. having a training set that matches reality vs images that were captured and available ~2020.
The larger base models do an excellent job of aging, try out asking for ages increased by 5 year increments, and you’ll see clear progression (some of it caricatured of course), e.g. “55 year old woman” vs “woman”.
Yeah, I mean it's not great that the models are biased around a certain subset of "woman" (usually young, pretty, white etc.) but you can just describe what you want to see and push the model to give it you. Yes, sometimes it's a bit of a fight, but it's doable.
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Not really, I'm in my sixties, and it's surprisingly difficult to get round the biases these models have of young, perfect people, if you want to get images of older people.
Try the single word prompt 'woman' and see what you get...
Have larger diffusion models gotten to synthetic training dogfooding yet?
The irony is that once we get there, we can address biases in historical data. I.e. having a training set that matches reality vs images that were captured and available ~2020.
The larger base models do an excellent job of aging, try out asking for ages increased by 5 year increments, and you’ll see clear progression (some of it caricatured of course), e.g. “55 year old woman” vs “woman”.
so put "old woman" then.
Yeah, I mean it's not great that the models are biased around a certain subset of "woman" (usually young, pretty, white etc.) but you can just describe what you want to see and push the model to give it you. Yes, sometimes it's a bit of a fight, but it's doable.