L Rowe, M Ethier, EH Dykhne… - Proceedings of the …, 2023 - openaccess.thecvf.com
Predicting the future motion of road agents is a critical task in an autonomous driving pipeline. In this work, we address the problem of generating a set of scene-level, or joint …
Reliable forecasting of the future behavior of road agents is a critical component to safe planning in autonomous vehicles. Here, we represent continuous trajectories as sequences …
C Jiang, A Cornman, C Park, B Sapp… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present MotionDiffuser, a diffusion based representation for the joint distribution of future trajectories over multiple agents. Such representation has several key advantages: first, our …
Y Zhu, D Luan, S Shen - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
Predicting future trajectories of surrounding agents is essential for safety-critical autonomous driving. Most existing work focuses on predicting marginal trajectories for each agent …
X Wang, T Su, F Da, X Yang - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
Motion forecasting is a key module in an autonomous driving system. Due to the heterogeneous nature of multi-sourced input, multimodality in agent behavior, and low …
Predicting future motions of road participants is an important task for driving autonomously in urban scenes. Existing models excel at predicting marginal trajectories for single agents, yet …
Perception and prediction are two separate modules in the existing autonomous driving systems. They interact with each other via hand-picked features such as agent bounding …
Making accurate motion prediction of the surrounding traffic agents such as pedestrians, vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion prediction …
Predicting the motion of multiple agents is necessary for planning in dynamic environments. This task is challenging for autonomous driving since agents (eg vehicles and pedestrians) …