Name
Title | ||
|---|---|---|
Improving Head Pose Estimation with a Combined Loss and Bounding Box Margin Adjustment |
Abstract | ||
|---|---|---|
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. The Tensorflow implementation of our work is available at https://github.com/MingzhenShao/HeadPose. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/FG.2019.8756605 | 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019) |
Keywords | Field | DocType |
combined loss,bounding box margin adjustment,RGB image,detected face,loss functions,head pose estimation,CNN | Computer vision,Computer science,Rgb image,Pose,Artificial intelligence,Minimum bounding box | Journal |
Volume | ISSN | ISBN |
abs/1905.08609 | 2326-5396 | 978-1-7281-0090-6 |
Citations | PageRank | References |
1 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingzhen Shao | 1 | 1 | 0.34 |
| Zhun Sun | 2 | 12 | 3.49 |
| Mete Ozay | 3 | 106 | 14.50 |
| Takayuki Okatani | 4 | 492 | 50.10 |