Joint Cascade Face Detection and Alignment
| 
49 | 
34 | 
0
Abstract
We present a new state-of-the-art approach for face detec- tion. The key idea is to combine face alignment with detection, observing that aligned face shapes provide better features for face classification. To make this combination more effective, our approach learns the two tasks jointly in the same cascade framework, by exploiting recent advances in face alignment. Such joint learning greatly enhances the capability of cascade detection and still retains its realtime performance. Extensive experiments show that our approach achieves the best accuracy on chal- lenging datasets, where all existing solutions are either inaccurate or too slow.
还没有评论，说两句吧！
热门资源
Learning to Predi...
Much of model-based reinforcement learning invo...
Stratified Strate...
In this paper we introduce Stratified Strategy ...
The Variational S...
Unlike traditional images which do not offer in...
A Mathematical Mo...
Direct democracy, where each voter casts one vo...
Rating-Boosted La...
The performance of a recommendation system reli...
智能在线
400-630-6780
聆听.建议反馈
E-mail: support@tusaishared.com
资源分类
