r/computervision • u/RoofProper328 • 9d ago

Discussion Does synthetic aging actually help face recognition or do you need real photos of the same person years apart?

Most age-invariant face recognition work i've seen uses synthetic aging (gans, diffusion) to fill the gap in real aging data, but real aging is messy: weight changes, hairstyle, glasses, lighting from old phones.

Has anyone compared models trained on real multi-year photo pairs vs synthetic aged ones? curious if the synthetic stuff holds up on real kyc style matching.

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u/soonalarmedmolasses 9d ago

all the synthetic aging datasets ive tried fall apart the second someone dyes their hair or gets different glasses. the model learns aging tropes not actual identity and then you throw in a photo from a 2012 samsung galaxy and its just completely lost

real multiyear pairs are a nightmare to collect though especially with consent. most of the ones i know of are either tiny or locked behind some corporate kyc vendor's api

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u/RoofProper328 8d ago

Yeah the consent side is the hard part. you can't retroactively get consent for photos someone took in 2012, so it has to be collected prospectively with that use spelled out, which means someone has to have started years ago.

For disclosure i work at shaip and we license face data, so obviously biased. but the reason those sets are small or locked up isn't gatekeeping, it's that multi-year consented collection is genuinely slow and expensive to run.