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Found 3 papers, 1 papers with code
Human Motion Prediction under Unexpected Perturbation
We investigate a new task in human motion prediction, which is predicting motions under unexpected physical perturbation potentially involving multiple people.
Human Trajectory Forecasting with Explainable Behavioral Uncertainty
Model-free methods offer superior prediction accuracy but lack explainability, while model-based methods provide explainability but cannot predict well.
Human Trajectory Prediction via Neural Social Physics
Our new model (Neural Social Physics or NSP) is a deep neural network within which we use an explicit physics model with learnable parameters.
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Trajectory Prediction
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