Name
Abstract | ||
|---|---|---|
In recent years, with the increase of video surveillance equipment, the amount of video data and complexity are growing. How to obtain structured data has become a problem. In surveillance videos, people extremely want to obtain valuable information about the position and characteristics of pedestrians, such as the pedestrian’s gender, age, appearance. Therefore, as a basic computer vision task, p... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SWC50871.2021.00084 | 2021 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI) |
Keywords | DocType | ISBN |
Pedestrian detection,Attribute recognition,YOLOv3,Integrated | Conference | 978-1-6654-1236-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ye Li | 1 | 61 | 7.26 |
| Zhaoqian Jia | 2 | 0 | 0.68 |
| Yiyin Ding | 3 | 0 | 0.68 |
| Fangyan Shi | 4 | 0 | 0.34 |
| Guangqiang Yin | 5 | 2 | 5.79 |