UMDFaces: An annotated face dataset for training deep networks

@article{Bansal2016UMDFacesAA,
  title={UMDFaces: An annotated face dataset for training deep networks},
  author={Ankan Bansal and Anirudh Nanduri and Carlos D. Castillo and Rajeev Ranjan and Rama Chellappa},
  journal={2017 IEEE International Joint Conference on Biometrics (IJCB)},
  year={2016},
  pages={464-473}
}
Highlight Information
Recent progress in face detection (including keypoint detection), and recognition is mainly being driven by (i) deeper convolutional neural network architectures, and (ii) larger datasets. [...] Key Method We discuss how a large dataset can be collected and annotated using human annotators and deep networks. We provide human curated bounding boxes for faces. We also provide estimated pose (roll, pitch and yaw), locations of twenty-one key-points and gender information generated by a pre-trained neural network…Expand Abstract

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