Name
Abstract | ||
|---|---|---|
In this paper, we present a deep regression approach for face alignment. The deep regressor is a neural network that consists of a global layer and multistage local layers. The global layer estimates the initial face shape from the whole image, while the following local layers iteratively update the shape with local image observations. Combining standard derivations and numerical approximations, w... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TNNLS.2016.2618340 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Shape,Face,Feature extraction,Estimation,Computational modeling,Learning systems,Deformable models | Differential (mechanical device),Regression,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Backpropagation,Artificial neural network,Machine learning | Journal |
Volume | Issue | ISSN |
29 | 1 | 2162-237X |
Citations | PageRank | References |
6 | 0.42 | 39 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baoguang Shi | 1 | 630 | 20.83 |
| Xiang Bai | 2 | 3517 | 149.87 |
| Wenyu Liu | 3 | 3131 | 170.07 |
| Jingdong Wang | 4 | 4198 | 156.76 |