MobileFAN: Transferring deep hidden representation for face alignment

作者：

Highlights：

• A simple and lightweight network, namely Mobile Face Alignment Network (MobileFAN), is proposed for facial landmark detection.

• It can effectively handle face alignment problem in high accuracy with only 8% of the model size of state-of-the-art models.

• This is the first attempt to introduce knowledge distillation techniques to heatmap regression-based method for performance enhancement in face alignment.

• The experimental results on three public available datasets demonstrate the effectiveness and superiority of the proposed model.

摘要

•A simple and lightweight network, namely Mobile Face Alignment Network (MobileFAN), is proposed for facial landmark detection.•It can effectively handle face alignment problem in high accuracy with only 8% of the model size of state-of-the-art models.•This is the first attempt to introduce knowledge distillation techniques to heatmap regression-based method for performance enhancement in face alignment.•The experimental results on three public available datasets demonstrate the effectiveness and superiority of the proposed model.

论文关键词：Face alignment,Knowledge distillation,Lightweight model

论文评审过程：Received 8 May 2019, Revised 4 October 2019, Accepted 15 November 2019, Available online 19 November 2019, Version of Record 28 November 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.107114