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SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction

Description

Predicting the future motion of surrounding agents is essential for autonomous vehicles (AVs) to operate safely in dynamic, human-robot-mixed environments. Context information, such as road maps and surrounding agents' states, provides crucial geometric and semantic information for motion behavior prediction. To this end, recent works explore two-stage prediction frameworks where coarse trajectories are first proposed, and then used to select critical context information for trajectory refinemen

Source

http://arxiv.org/abs/2403.11492v2