SOTAVerified

Trajectory Forecasting

Trajectory forecasting is a sequential prediction task, where a forecasting model predicts future trajectories of all moving agents (humans, vehicles, etc.) in a scene, based on their past trajectories and/or the scene context.

(Illustrative figure from Social NCE: Contrastive Learning of Socially-aware Motion Representations)

Papers

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Showing 176–187 of 187 papers

TitleStatusHype
Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets—0
Back to square one: probabilistic trajectory forecasting without bells and whistles—0
The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal GraphsCode0
Learning Gibbs-regularized GANs with variational discriminator reparameterization—0
Machine Learning for Spatiotemporal Sequence Forecasting: A Survey—0
SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical ConstraintsCode0
MX-LSTM: mixing tracklets and vislets to jointly forecast trajectories and head poses—0
Social GAN: Socially Acceptable Trajectories with Generative Adversarial NetworksCode1
“Seeing is Believing”: Pedestrian Trajectory Forecasting Using Visual Frustum of Attention—0
CAR-Net: Clairvoyant Attentive Recurrent Network—0
First-Person Activity Forecasting with Online Inverse Reinforcement Learning—0
Forecasting Social Navigation in Crowded Complex Scenes—0
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