Conference Paper/Proceeding/Abstract 1787 views 305 downloads
Nested Shallow CNN-Cascade for Face Detection in the Wild
Jingjing Deng,
Xianghua Xie 
2017 IEEE 12th International Conference on Automatic Face & Gesture Recognition, Pages: 165 - 172
Swansea University Authors:
Jingjing Deng, Xianghua Xie
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DOI (Published version): 10.1109/FG.2017.29
Abstract
We propose a nested CNN-cascade learning algorithm that adopts shallow neural network architectures that allow efficient and progressive elimination of negative hypothesis from easy to hard via self-learning discriminative representations from coarse to fine scales. The face detection problem is con...
| Published in: | 2017 IEEE 12th International Conference on Automatic Face & Gesture Recognition |
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| ISBN: | 978-1-5090-4024-7 978-1-5090-4023-0 |
| Published: |
IEEE
2017
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| Online Access: |
http://csvision.swan.ac.uk/uploads/Site/Publication/jd17fg.pdf |
| URI: | https://cronfa.swan.ac.uk/Record/cronfa32108 |
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| Abstract: |
We propose a nested CNN-cascade learning algorithm that adopts shallow neural network architectures that allow efficient and progressive elimination of negative hypothesis from easy to hard via self-learning discriminative representations from coarse to fine scales. The face detection problem is considered as solving three sub-problems: eliminating easy background with a simple but fast model, then localising the face region with a soft-cascade, followed by precise detection and localisation by verifying retained regions with a deeper and stronger model. |
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| Keywords: |
Deep Learning, Neural Network, Face Detection, CNN |
| College: |
Faculty of Science and Engineering |
| Start Page: |
165 |
| End Page: |
172 |