Actually, that's only one of the contributions, and I'm not so sure it's the "key innovation". Every other recent face recognition method also tries to do some kind of alignment to make faces more similar in pose/expression/lighting prior to classifying them; and of these, several also fit faces to a 3-d model to rotate to frontal (with varying quality).

See my other comment for my guess on what's actually providing the boost: https://news.ycombinator.com/item?id=7393378