Name
Abstract | ||
|---|---|---|
In this letter, we propose a novel approach for agent motion prediction in cluttered environments. One of the main challenges in predicting agent motion is accounting for location and context-specific information. Our main contribution is the concept of learning context maps to improve the prediction task. Context maps are a set of location-specific latent maps that are trained alongside the predi... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LRA.2020.3004800 | IEEE Robotics and Automation Letters |
Keywords | DocType | Volume |
Intelligent vehicles,prediction methods | Journal | 5 |
Issue | ISSN | Citations |
4 | 2377-3766 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Igor Gilitschenski | 1 | 78 | 13.89 |
| Guy Rosman | 2 | 174 | 18.86 |
| Gupta Arjun | 3 | 0 | 0.34 |
| Sertac Karaman | 4 | 1190 | 87.27 |
| Daniela Rus | 5 | 7128 | 657.33 |