4 papers
Generative Active Learning for Long-tail Trajectory Prediction via Controllable Diffusion Model
Daehee Park, Monu Surana, Pranav Desai +3
While data-driven trajectory prediction has enhanced the reliability of autonomous driving systems, it still struggles with rarely observed long-tail scenarios. Prior works address…
Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planning
Giwon Lee, Wooseong Jeong, Daehee Park +2
Motion planning is a crucial component of autonomous robot driving. While various trajectory datasets exist, effectively utilizing them for a target domain remains challenging due…
Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning
Giwon Lee, Daehee Park, Jaewoo Jeong +1
Safe and effective motion planning is crucial for autonomous robots. Diffusion models excel at capturing complex agent interactions, a fundamental aspect of decision-making in dyna…
Multi-modal Knowledge Distillation-based Human Trajectory Forecasting
Jaewoo Jeong, Seohee Lee, Daehee Park +2
Pedestrian trajectory forecasting is crucial in various applications such as autonomous driving and mobile robot navigation. In such applications, camera-based perception enables t…