  We address a problem of estimating pose of a person's head from its RGB
image. The employment of CNNs for the problem has contributed to significant
improvement in accuracy in recent works. However, we show that the following
two methods, despite their simplicity, can attain further improvement: (i)
proper adjustment of the margin of bounding box of a detected face, and (ii)
choice of loss functions. We show that the integration of these two methods
achieve the new state-of-the-art on standard benchmark datasets for in-the-wild
head pose estimation.
