It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction

Understand

Human trajectory forecasting with multiple socially interacting agents is of critical importance for autonomous navigation in human environments, e.g., for self-driving cars and social robots.

• In this work, we present Predicted Endpoint Conditioned Network (PECNet) for flexible human trajectory prediction.
• PECNet infers distant trajectory endpoints to assist in long-range multi-modal trajectory prediction.
• A novel non-local social pooling layer enables PECNet to infer diverse yet socially compliant trajectories.