… boxes as supervision [2], in trajectory prediction we only observe one ground truth future …
goal set predictor for goal set prediction. The optimization algorithm finds an optimal goal set …

… trajectory prediction. Our approach relies on using lane centerlines captured in rich maps of
the environment to generate a set of proposed goal … predict a set of goal-based trajectories …

… trajectory estimation. To this end, we present a recurrent network for trajectory prediction,
called Stepwise Goal-… The hidden size is set to 128, since we only need a lightweight module to …

… to predict pedestrian trajectories via the guidance of goal ex… modest expense through a
novel goal-search mechanism on … for goal-based trajectory prediction assesses an initial set of …

… With the objective of longterm prediction, we extend this setting into maximal future
distance possible supported by the dataset. This results in the settings of observing 8 and …

… between predicted and ground truth trajectories, … setting, we report Min20ADE and Min20FDE
metrics, which are obtained by generating 20 predicted samples for each input trajectory …

… a sub-goal tree, and building on it, we develop new methods for trajectory prediction, learning,
… We show that in a supervised learning setting, sub-goal trees better account for trajectory …

… Our work highlights a new direction for goal-based trajectory prediction by estimating …
set the coarse trajectory prediction number M to 200 and on Argoverse, we set M to 60. We …

… agents to share their past trajectory, goal, and intention information … In our experiments, we
set q = 4, thus predicting short-term … Goalgan: Multimodal trajectory prediction based on goal …

… of the intended goal, and is focused primarily on the long-term trajectory of the agent. We …
set. Results show the benefits of our method in comparison to traditional trajectory prediction …