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 …
Z Zhou, L Ye, J Wang, K Wu… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Accurately predicting the future motions of surrounding traffic agents is critical for the safety of autonomous vehicles. Recently, vectorized approaches have dominated the motion …
S Ettinger, S Cheng, B Caine, C Liu… - Proceedings of the …, 2021 - openaccess.thecvf.com
As autonomous driving systems mature, motion forecasting has received increasing attention as a critical requirement for planning. Of particular importance are interactive …
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) …
Multi-agent trajectory forecasting in autonomous driving requires an agent to accurately anticipate the behaviors of the surrounding vehicles and pedestrians, for safe and reliable …
Multi-agent motion prediction is challenging because it aims to foresee the future trajectories of multiple agents (eg pedestrians) simultaneously in a complicated scene. Existing work …
Reliable multi-agent trajectory prediction is crucial for the safe planning and control of autonomous systems. Compared with single-agent cases, the major challenge in …
Abstract Reasoning about human motion is an important prerequisite to safe and socially- aware robotic navigation. As a result, multi-agent behavior prediction has become a core …
C Tang, RR Salakhutdinov - Advances in neural information …, 2019 - proceedings.neurips.cc
Temporal prediction is critical for making intelligent and robust decisions in complex dynamic environments. Motion prediction needs to model the inherently uncertain future …