Title: Performance evaluation of face alignment algorithms on "in-the-wild" selfies
Authors: Babanin, Ivan
Mashrabov, Aleksandr
Citation: WSCG '2018: short communications proceedings: The 26th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2016 in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech Republic May 28 - June 1 2018, p. 70-77.
Issue Date: 2018
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: wscg.zcu.cz/WSCG2018/!!_CSRN-2802.pdf
ISBN: 978-80-86943-41-1
ISSN: 2464-4617
Keywords: benchmark testování;obličej;tvar;strojové učení;robustní měření;mobilní zařízení;zarovnání obličeje
Keywords in different language: benchmark testing;face;shape;machine learning;robust measurement;mobile devices;face alignment
Abstract: Recently mobile apps, which beautify human face or apply cute masks to a human face, become very popular and gain lots of attention in media. These tasks require very precise landmarks localization to avoid "uncanny valley" effect. We introduce the new dataset of selfies, that were taken on mobile devices, and robustly evaluate and compare different state-of-the-art approaches to the task of face alignment. Evidently, our dataset allows to reliably rank face alignment algorithms that is superior to the most popular dataset in that area of research.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG '2018: Short Papers Proceedings

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/34658

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