Learning to Infer Relations for Future Trajectory Forecast
Conference on Computer Vision and Pattern Recognition Workshop (CVPRW) 2019
Inferring relational behavior between road users as well as road users and their surrounding physical space is an important step toward effective modeling and prediction of navigation strategies adopted by participants in road scenes. To this end, we propose a relation-aware frame-work for future trajectory forecast, which aims to infer relational information from the interactions of road users with each other and with environments. Extensive evaluations on a public dataset demonstrate the robustness of the proposed framework as observed by performances higher than the state-of-the-art methods.