Name
Abstract | ||
|---|---|---|
Vehicle detection, tracking and motion forecasting are critical for intelligent vehicle sensing system. In this paper, we propose a single-stage deep neural network (DNN) called TAPNet, which combines consecutive frames of LiDAR scans and high-definition (HD) maps to jointly reason about Bird's Eye View (BEV) detection and trajectory prediction of vehicles. In our proposed method, an auxiliary pas... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IV48863.2021.9575776 | 2021 IEEE Intelligent Vehicles Symposium (IV) |
Keywords | DocType | ISSN |
Laser radar,Tracking,Intelligent vehicles,Vehicle detection,Training data,Predictive models,Trajectory | Conference | 1931-0587 |
ISBN | Citations | PageRank |
978-1-7281-5394-0 | 1 | 0.41 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhicheng Zhang | 1 | 1 | 1.09 |
| Yafei Wang | 2 | 1 | 0.41 |
| Xulei Liu | 3 | 1 | 0.41 |