Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild

Zhenhua Feng, Josef Kittler, Muhammad Awais, Patrik Huber, Xiaojun Wu

CVPRW 2017 pp. 2106-2115

doi:10.1109/CVPRW.2017.262 /cvprw/2017/feng2017cvprw-face/

Abstract

We present a framework for robust face detection and landmark localisation of faces in the wild, which has been evaluated as part of `the 2nd Facial Landmark Localisation Competition'. The framework has four stages: face detection, bounding box aggregation, pose estimation and landmark localisation. To achieve a high detection rate, we use two publicly available CNN-based face detectors and two proprietary detectors. We aggregate the detected face bounding boxes of each input image to reduce false positives and improve face detection accuracy. A cascaded shape regressor, trained using faces with a variety of pose variations, is then employed for pose estimation and image pre-processing. Last, we train the final cascaded shape regressor for fine-grained landmark localisation, using a large number of training samples with limited pose variations. The experimental results obtained on the 300W and Menpo benchmarks demonstrate the superiority of our framework over state-of-the-art methods.

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Cite

Text

Feng et al. "Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017. doi:10.1109/CVPRW.2017.262

Markdown

[Feng et al. "Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017.](https://mlanthology.org/cvprw/2017/feng2017cvprw-face/) doi:10.1109/CVPRW.2017.262

BibTeX

@inproceedings{feng2017cvprw-face,
  title     = {{Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild}},
  author    = {Feng, Zhenhua and Kittler, Josef and Awais, Muhammad and Huber, Patrik and Wu, Xiaojun},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2017},
  pages     = {2106-2115},
  doi       = {10.1109/CVPRW.2017.262},
  url       = {https://mlanthology.org/cvprw/2017/feng2017cvprw-face/}
}