> Intuitively this feels a bit off, since outputting a discretized 3d model instead of fitting a continuous model has inherent resolution limitations, but the benchmark results are pretty impressive.
Isn't this because deep learning is in fact a type of interpolation?
And another question: are there any techniques based on neural networks that combine multiple images into the most plausible model?
No The output is still discrete.
> And another question: are there any techniques based on neural networks that combine multiple images into the most plausible model?
Could work.
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Here is the same image used as input for 3d face reconstruction using both methods:
Left side is morphable face model (EOS by Patrik Huber).
Right side is this new CNN voxels method.
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Here is live 3D model on the authors' site:
http://www.cs.nott.ac.uk/~psxasj/3dme/view.php?name=../59b41...