Multi Future Trajectory Prediction
6 papers with code • 2 benchmarks • 3 datasets
Most implemented papers
It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction
In this work, we present Predicted Endpoint Conditioned Network (PECNet) for flexible human trajectory prediction.
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
DESIRE effectively predicts future locations of objects in multiple scenes by 1) accounting for the multi-modal nature of the future prediction (i. e., given the same context, future may vary), 2) foreseeing the potential future outcomes and make a strategic prediction based on that, and 3) reasoning not only from the past motion history, but also from the scene context as well as the interactions among the agents.
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction
The first contribution is a new dataset, created in a realistic 3D simulator, which is based on real world trajectory data, and then extrapolated by human annotators to achieve different latent goals.
AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction
Anticipating human motion in crowded scenarios is essential for developing intelligent transportation systems, social-aware robots and advanced video surveillance applications.
MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction
Autonomous vehicles are expected to drive in complex scenarios with several independent non cooperating agents.
Multi-Agent Trajectory Prediction With Heterogeneous Edge-Enhanced Graph Attention Network
Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential for safe and efficient operation of connected automated vehicles under complex driving situations.