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The end result exhibits that for a similar feed-forward neural network when our approach is used to introduce facial landmark details right into a CNN, precision increases from 88.5% to 99.0% and imply typical mistake decreases from 5.ninety four° to one.forty six° on AFLW2000-3D. Furthermore, we evaluate our approach on quite a few datasets

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