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Found 6 papers, 4 papers with code
SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction
Analyzing and forecasting trajectories of agents like pedestrians and cars in complex scenes has become more and more significant in many intelligent systems and applications.
Another Vertical View: A Hierarchical Network for Heterogeneous Trajectory Prediction via Spectrums
In this paper, we bring a new ``view'' for trajectory prediction to model and forecast trajectories hierarchically according to different frequency portions from the spectral domain to learn to forecast trajectories by considering their frequency responses.
CSCNet: Contextual Semantic Consistency Network for Trajectory Prediction in Crowded Spaces
The current methods are dedicated to studying the agents' future trajectories under the social interaction and the sceneries' physical constraints.
View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums
Different frequency bands in the trajectory spectrums could hierarchically reflect agents' motion preferences at different scales.
Ranked #3 on
Trajectory Prediction
on ETH/UCY
MSN: Multi-Style Network for Trajectory Prediction
Then, we assume that the target agents may plan their future behaviors according to each of these categorized styles, thus utilizing different style channels to make predictions with significant style differences in parallel.
BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction
Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors.
