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authorJules Laplace <julescarbon@gmail.com>2018-11-25 22:19:15 +0100
committerJules Laplace <julescarbon@gmail.com>2018-11-25 22:19:15 +0100
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+Robust face landmark estimation under occlusion|http://scholar.google.com/https://www.cv-foundation.org/openaccess/content_iccv_2013/html/Burgos-Artizzu_Robust_Face_Landmark_2013_ICCV_paper.html|2013|441|16|6035683787196907858|None|http://scholar.google.com/scholar?cites=6035683787196907858&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=6035683787196907858&hl=en&as_sdt=0,5|None|Human faces captured in real-world conditions present large variations in shape and occlusions due to differences in pose, expression, use of accessories such as sunglasses and hats and interactions with objects (eg food). Current face landmark estimation approaches struggle under such conditions since they fail to provide a principled way of handling outliers. We propose a novel method, called Robust Cascaded Pose Regression (RCPR) which reduces exposure to outliers by detecting occlusions explicitly and using …