Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
526760 | Image and Vision Computing | 2016 | 9 Pages |
Abstract
•We show how to achieve state-of-the-art facial landmark localization by CNN.•The system's performance is improved by deeper network.•We show our system's performance is close to human.
In this paper we present our solution to the 300 Faces in the Wild Facial Landmark Localization Challenge. We demonstrate how to achieve very competitive localization performance with a simple deep learning based system. Human study is conducted to show that the accuracy of our system has been very close to human performance. We discuss how this finding would affect our future direction to improve our system.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Haoqiang Fan, Erjin Zhou,