5 August 2019
Lei Ju, Xiangyu Zhu, Zhen Lei, Xinfang Cui, Wankou Yang, Changyin Sun - 34rd Youth Academic Annual Conference of Chinese Association of Automation, 2019
Databases are of great significance to researchers to achieve a satisfactory model. The lack of data is always a bottleneck to facial landmark localization, especially for the dense facial landmark detection. In this article, we provide a new dataset, called Dense Landmark Localization (DLL) database, which contains 39,198 images and is annotated in high quality. Annotating dense landmarks is a very tedious work due to two challenges. (a) Not every facial point has clear definition. Some of them distribute uniformly along the contour. Their labelled positions are determined by subjective judgement of the annotators, so that the quality of the annotation is poor. (b) Adjusting facial points one by one is time-consuming. The workload will increase dramatically when there are more points. To overcome the aforementioned problems, we propose a semiautomatic annotation tool to annotate dense points with much less clicks.
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