Abstract
Sparse facial landmark localization has lower precision for face reconstruction, while more point landmarks are competent to depict the structure of facial components. In this paper, the pipeline of detecting 106-point facial landmarks with regression is proposed. Based on the convergence and practical application of multi-points regression, we design MobileNetV2-FL and VGG16-FL. Besides, an effective data preprocessing strategy and some training tricks, such as the Online Hard Example Mining algorithm and Wing loss are applied to the issue. Experimental results show that the proposed method has lower failure rate, and is an effective and robust facial landmark localization method.
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Acknowledgments
This work is supported by National Science Foundation of China (No. 61573356) and National Key R&D Program of China (2018YFB0504900).
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Zhai, X., He, Y., Zhao, Q., Ding, Y. (2019). 106-Point Facial Landmark Localization with Mobile Networks Based on Regression. In: Sun, Z., He, R., Feng, J., Shan, S., Guo, Z. (eds) Biometric Recognition. CCBR 2019. Lecture Notes in Computer Science(), vol 11818. Springer, Cham. https://doi.org/10.1007/978-3-030-31456-9_32
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DOI: https://doi.org/10.1007/978-3-030-31456-9_32
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