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Volume: 32 | Article ID: art00007
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A Local-Global Aggregate Network for Facial Landmark Localization
  DOI :  10.2352/ISSN.2470-1173.2020.8.IMAWM-185  Published OnlineJanuary 2020
Abstract

Facial landmark localization plays a critical role in many face analysis tasks. In this paper, we present a novel local-global aggregate network (LGA-Net) for robust facial landmark localization of faces in the wild. The network consists of two convolutional neural network levels which aggregate local and global information for better prediction accuracy and robustness. Experimental results show our method overcomes typical problems of cascaded networks and outperforms state-of-the-art methods on the 300-W [1] benchmark.

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Ruiyi Mao, Qian Lin, Jan P. Allebach, "A Local-Global Aggregate Network for Facial Landmark Localizationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World,  2020,  pp 185-1 - 185-6,  https://doi.org/10.2352/ISSN.2470-1173.2020.8.IMAWM-185

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