
3D Face Reconstruction with Position Map Regression Networks - austin_kodra
https://heartbeat.fritz.ai/3d-face-reconstruction-with-position-map-regression-networks-36f0ac2d3ef1
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yodon
To my human eye the facial landmark placement in this paper looks much better
than the 3D reconstructions (which look pretty poor compared to the facial
shapes a human eye or human artist would interpret from the photos). The
authors argue that their approach isn’t limited by the explicit finite number
of facial basis functions problem encountered in most prior 3D reconstruction
work, but they seem to neglect that because of the finite size of the ground
truth 3D scan dataset their approach is still limited in exactly the same way,
it’s just limited implicitly rather than explicitly. If you don’t have enough
ground truth scan data for black or Asian or Slavic or etc. faces, the network
can’t learn to represent them correctly and you end up with the same low-
dimensional results as the prior work, you’ve just hidden the low
dimensionality from view by burying it in your neural layers rather than
making it explicit in a set of easily identifiable basis functions. Sure, if
these authors had a larger ground truth dataset they could do better, but so
could the explicit basis function methods.

Again, the facial landmark detection looks great, my concerns are purely with
the inaccuracy of the 3D model reconstructions.

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bwang29
Next - select your own cast for the movie you're about to watch.

~~~
John_KZ
Sooner than later you will be able to spontaneously generate films from books
or scripts. You will then do some high-level editing by clicking through
latent spaces, and voila, you have your own Hollywood-grade film. It's gonna
be weird.

~~~
simcop2387
Then it's just a short step to creating new stories in a known style:

    
    
        LAFORGE: Computer, in the Holmesian style, create a mystery to confound Data with an opponent who has the ability to defeat him.
        COMPUTER: Define parameters of programme.
        PULASKI: What does that mean?
        LAFORGE: Computer wants to know how far to take the game.
        PULASKI: You mean it's giving you a chance to limit your risk.
        LAFORGE: No, the parameters will be whatever is necessary in order to accomplish the directive. Create an adversary capable of defeating Data.
    

We're steadily approaching science fiction when it comes to creating things
like this.

