Name
Abstract | ||
|---|---|---|
Predicting future trajectories of traffic agents in highly interactive environments is an essential and challenging problem for the safe operation of autonomous driving systems. On the basis of the fact that self-driving vehicles are equipped with various types of sensors (e.g., LiDAR scanner, RGB camera, radar, etc.), we propose a Cross-Modal Embedding framework that aims to benefit from the use ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CVPR46437.2021.00031 | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |
Keywords | DocType | ISSN |
Training,Laser radar,Roads,Predictive models,Linear programming,Feature extraction,Data models | Conference | 1063-6919 |
ISBN | Citations | PageRank |
978-1-6654-4509-2 | 4 | 0.41 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chiho Choi | 1 | 36 | 5.61 |
| Joon Hee Choi | 2 | 4 | 0.41 |
| jiachen li | 3 | 24 | 7.21 |
| Srikanth Malla | 4 | 6 | 2.48 |