Search Results for author:
Found 3 papers, 1 papers with code
LG-Traj: LLM Guided Pedestrian Trajectory Prediction
We introduce LG-Traj, a novel approach incorporating LLMs to generate motion cues present in pedestrian past/observed trajectories.
Improving Trajectory Prediction in Dynamic Multi-Agent Environment by Dropping Waypoints
Motion prediction systems must effectively learn spatial and temporal information from the past to forecast the future trajectories of the agent.
Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey
End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with modular systems, such as their overwhelming complexity and propensity for error propagation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
