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 91–100 of 187 papers

TitleStatusHype
Probabilistic Symmetry for Multi-Agent DynamicsCode0
Goal-driven Self-Attentive Recurrent Networks for Trajectory PredictionCode1
PreTraM: Self-Supervised Pre-training via Connecting Trajectory and MapCode1
SMEMO: Social Memory for Trajectory Forecasting—0
Under the Hood of Transformer Networks for Trajectory Forecasting—0
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting—0
Social-DualCVAE: Multimodal Trajectory Forecasting Based on Social Interactions Pattern Aware and Dual Conditional Variational Auto-Encoder—0
Trajectory Forecasting from Detection with Uncertainty-Aware Motion Encoding—0
CVAE-H: Conditionalizing Variational Autoencoders via Hypernetworks and Trajectory Forecasting for Autonomous Driving—0
Intelligent Camera Selection Decisions for Target Tracking in a Camera NetworkCode0
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