The Mobiface Dataset

Face tracking serves as the crucial initial step in mobile applications trying to analyse target faces over time in mobile settings. However, this problem has received little attention, mainly due to the scarcity of dedicated face tracking benchmarks. In this work, we introduce MobiFace, the first dataset for single face tracking in mobile situations. It consists of 80 unedited live-streaming mobile videos captured by 70 different smartphone users in fully unconstrained environments. Over 95K bounding boxes are manually labelled. The videos are carefully selected to cover typical smartphone usage. The videos are also annotated with 14 attributes, including 6 newly proposed attributes and 8 commonly seen in object tracking.

 

For downloading data, evaluation tools and benchmark results, please visit https://mobiface.github.io/.


If you use this data, we kindly request you to cite the following paper:
@misc{lin2018mobiface,
title={MobiFace: A Novel Dataset for Mobile Face Tracking in the Wild},
author={Yiming Lin and Shiyang Cheng and Jie Shen and Maja Pantic},
year={2018},
eprint={1805.09749},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/1805.09749v2}
}