期刊
2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW)
卷 -, 期 -, 页码 2116-2125出版社
IEEE
DOI: 10.1109/CVPRW.2017.263
关键词
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资金
- FiDiPro program of Tekes [1849/31/2015]
- EPSRC [EP/N007743/1]
- EPSRC DTA award at Imperial College London
- Imperial College London
- EPSRC [EP/N007743/1] Funding Source: UKRI
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, run 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. The results of the Menpo challenge demonstrate that recent deep learning architectures when trained with the abundance of data lead to excellent results. Finally, we discuss directions for future benchmarks in the topic.
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