This folder contains a copy of the AFLW-mtfl dataset [1], [2] to help reproduce the results of the paper:
James Thewlis, Samuel Albanie, Hakan Bilen, Andrea Vedaldi. Unsupervised learning of landmarks via vector exchange. ICCV 2019
Tar contents
The original AFLW contains around 25k images with up to 21 landmarks. For the purposes of evaluating five-landmark detectors, the authors of TCDCN introduced a test subset of almost 3K faces.
The compressed tar file (252 MiB) can be downloaded from:
http:/www.robots.ox.ac.uk/~vgg/research/DVE/data/datasets/aflw-mtfl.tar.gz
sha1sum: 885b09159c61fa29998437747d589c65cfc4ccd3
A list of the contents of the tar file are given in tar_include.txt.
The original datasets can also be downloaded from the links below:
- AFLW https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/
- MTFL cropped images http://mmlab.ie.cuhk.edu.hk/projects/TCDCN/data/MTFL.zip
If you use the AFLW dataset, in particular with MTFL split, please cite the following papers:
@inproceedings{koestinger2011annotated,
title={Annotated facial landmarks in the wild: A large-scale, real-world database for facial landmark localization},
author={Koestinger, Martin and Wohlhart, Paul and Roth, Peter M and Bischof, Horst},
booktitle={2011 IEEE international conference on computer vision workshops (ICCV workshops)},
pages={2144--2151},
year={2011},
organization={IEEE}
}
@inproceedings{zhang2014facial,
title={Facial landmark detection by deep multi-task learning},
author={Zhang, Zhanpeng and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},
booktitle={European conference on computer vision},
pages={94--108},
year={2014},
organization={Springer}
}