The Menpo Facial Landmark Localisation Challenge: A Step Towards the Solution

Stefanos Zafeiriou, George Trigeorgis, Grigorios Chrysos, Jiankang Deng, Jie Shen; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017, pp. 170-179

Abstract


In this paper, we present a new benchmark (Menpo benchmark) for facial landmark localisation and summarise the results of the recent competition, so-called Menpo Challenge, held in conjunction to CVPR 2017. The Menpo benchmark, contrary to the previous benchmarks such as 300-W and 300-VW, contains facial images both in (nearly) frontal, as well as in profile pose (annotated with a different markup of facial landmarks). Furthermore, we increase considerably the number of annotated images so that deep learning algorithms can be robustly applied to the problem.

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[bibtex]
@InProceedings{Zafeiriou_2017_CVPR_Workshops,
author = {Zafeiriou, Stefanos and Trigeorgis, George and Chrysos, Grigorios and Deng, Jiankang and Shen, Jie},
title = {The Menpo Facial Landmark Localisation Challenge: A Step Towards the Solution},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {July},
year = {2017}
}