Technology of Graphic & Image
|
2856-2860

CASPN: cascaded spatial pyramid network for face landmark localization

Xie Jinheng
Zhang Yansheng
School of Electronic & Information Engineering, Guangdong Ocean University, Zhanjiang Guangdong 524088, China

Abstract

Focused on the issue that faces exposed in unconstrained environments within occlusion, shadow etc, and considered the efficient and speed of a neural network, this paper proposed a real-time and lightweight convolutional neural network for face alignment, which employed paralleled atrous convolution to capture larger and multi-scale receptive fields and cascaded spatial pyramid networks within feature fusion for refinement and context information for keypoints speculation. The model can be merely 10.6 MB and reach approximately 150 fps per face with high precision on GTX1080 device. Now, it achieves a good performance comparable to the state-of-the-art algorithms, 5.40% mean error and 7.36% failure rate on WFLW testset.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.05.0168
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 9
Section: Technology of Graphic & Image
Pages: 2856-2860
Serial Number: 1001-3695(2020)09-061-2856-05

Publish History

[2020-09-05] Printed Article

Cite This Article

谢金衡, 张炎生. CASPN:基于级联空间金字塔的人脸关键点定位网络 [J]. 计算机应用研究, 2020, 37 (9): 2856-2860. (Xie Jinheng, Zhang Yansheng. CASPN: cascaded spatial pyramid network for face landmark localization [J]. Application Research of Computers, 2020, 37 (9): 2856-2860. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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