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Found 3 papers, 1 papers with code
D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights
We present a trajectory prediction approach with respect to traffic lights, D2-TPred, which uses a spatial dynamic interaction graph (SDG) and a behavior dependency graph (BDG) to handle the problem of discontinuous dependency in the spatial-temporal space.
Sequential Multi-task Learning with Task Dependency for Appeal Judgment Prediction
SMAJudge utilizes two sequential components to model the complete proceeding from the lower court to the appellate court and employs an attention mechanism to make the prediction more explainable, which handles the challenges of AJP effectively.
SSAGCN: Social Soft Attention Graph Convolution Network for Pedestrian Trajectory Prediction
In detail, when modeling social interaction, we propose a new \emph{social soft attention function}, which fully considers various interaction factors among pedestrians.
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