Face alignment by coarse-to-fine shape searching
Refereed conference paper presented and published in conference proceedings


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AbstractWe present a novel face alignment framework based on coarse-to-fine shape searching. Unlike the conventional cascaded regression approaches that start with an initial shape and refine the shape in a cascaded manner, our approach begins with a coarse search over a shape space that contains diverse shapes, and employs the coarse solution to constrain subsequent finer search of shapes. The unique stage-by-stage progressive and adaptive search i) prevents the final solution from being trapped in local optima due to poor initialisation, a common problem encountered by cascaded regression approaches; and ii) improves the robustness in coping with large pose variations. The framework demonstrates real-time performance and state-of-the-art results on various benchmarks including the challenging 300-W dataset.
All Author(s) ListZhu S., Li C., Loy C.C., Tang X.
Name of ConferenceIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Start Date of Conference07/06/2015
End Date of Conference12/06/2015
Place of ConferenceBoston
Country/Region of ConferenceUnited States of America
Detailed descriptionorganized by IEEE Computer Society,
Year2015
Month10
Day14
Volume Number07-12-June-2015
Pages4998 - 5006
ISBN9781467369640
ISSN1063-6919
LanguagesEnglish-United Kingdom

Last updated on 2020-08-07 at 02:43