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 131–140 of 187 papers

TitleStatusHype
Res-GCNN: A Lightweight Residual Graph Convolutional Neural Networks for Human Trajectory Forecasting—0
Rethinking Trajectory Forecasting Evaluation—0
Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction—0
Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision—0
Robust Trajectory Forecasting for Multiple Intelligent Agents in Dynamic Scene—0
DIDER: Discovering Interpretable Dynamically Evolving Relations—0
Roundabout Dilemma Zone Data Mining and Forecasting with Trajectory Prediction and Graph Neural Networks—0
Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting—0
“Seeing is Believing”: Pedestrian Trajectory Forecasting Using Visual Frustum of Attention—0
Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting—0
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