Name
Abstract | ||
|---|---|---|
•Based on FPN, a training strategy is introduced for face detection, which increases the accuracy without adding additional computation cost.•A feature fusion module is designed to enhance the capability of feature extraction from the fused features.•Achieving superior performance over a number of state-of-the-art methods on the hard face detection while reaching a balance between the accuracy and speed. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2020.02.060 | Neurocomputing |
Keywords | DocType | Volume |
Face detection,Small face,Face feature fusion,Single shot detection,Efficiency-accuracy balance | Journal | 398 |
ISSN | Citations | PageRank |
0925-2312 | 2 | 0.41 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhenyu Fang | 1 | 3 | 1.77 |
| Jinchang Ren | 2 | 1144 | 88.54 |
| Stephen Marshall | 3 | 35 | 3.22 |
| Huimin Zhao | 4 | 206 | 23.43 |
| Zheng Wang | 5 | 43 | 4.79 |
| Kaizhu Huang | 6 | 2 | 0.41 |
| B. Xiao | 7 | 693 | 47.14 |