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MATRIX: Multi-Agent Trajectory Generation with Diverse Contexts
Data-driven methods have great advantages in modeling complicated human behavioral dynamics and dealing with many human-robot interaction applications.
Grouptron: Dynamic Multi-Scale Graph Convolutional Networks for Group-Aware Dense Crowd Trajectory Forecasting
Accurate, long-term forecasting of pedestrian trajectories in highly dynamic and interactive scenes is a long-standing challenge.
Online Learning in Planar Pushing with Combined Prediction Model
In this paper, we propose a combined prediction model and an online learning framework for planar push prediction.
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