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Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments
Detection and segmentation of moving obstacles, along with prediction of the future occupancy states of the local environment, are essential for autonomous vehicles to proactively make safe and informed decisions.
Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments
We can use driving data collected over a long period of time to extract rich information about how vehicles behave in different areas of the roads.
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