Abstract: While graph neural networks (GNNs) excel in graph data analysis, most methods rely on extensive labeled data, which is often impractical due to labeling costs and complexity. To address this ...
Abstract: Pedestrian trajectory prediction aims to forecast future movements based on historical paths. Spatial-temporal (ST) methods often separately model spatial interactions among pedestrians and ...
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