
Ask HN: Can Machine Learning Be Trained to Predict How Will I Look After 10 Yrs? - nanospeck
Just getting more curious on ML possibilites, if I train a model with thousands of potrait photo samples of people at age 20 and their photo at age 30. Can I create a model that can successfully predict how someone will look at 30 when given the photo at age 20?<p>Since I don&#x27;t have any mentors on this area. I am very interested to know atleast what this specific problem area is called in Machine Learning. Are there currently any frameworks you know that can do this?
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webmaven
Probably.

I am not aware of any work that checks how _accurate_ such age progression (or
regression) transforms are, but there are many papers that use the realism (as
evaluated by humans) of the results as a criteria.

As one example, here is a recent paper ( _Deep Feature Interpolation for Image
Content Changes_ ) that uses age progression as one of the evaluation tasks:
[https://arxiv.org/abs/1611.05507](https://arxiv.org/abs/1611.05507)

Regardless of the model you choose, if accuracy is your goal your training
data _may_ need 2+ images of each subject at different ages, labelled as to
age (and possibly year). You might not necessarily need to associate different
images of the same person with each other, you just need to give your system
the opportunity to learn more than just how a generic 16yo ages to a generic
37yo, etc.

As a bonus for having the images labelled by year, the same model should also
be able to transform a 1972 18yo into a 2012 18yo, etc.

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billconan
I think it is an interesting topic and may be possible.

But I see 2 difficulties. One is collecting this data. Maybe if you have
access to a passport photo database, things will be easier.

Second is how to design the cost function. direct comparing pixels doesn't
seem to be the right way.

a generative model sounds better.

