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Found 3 papers, 3 papers with code
Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning
Our model effectively handles the multi-modality of human motion and the complexity of long-term multi-agent interactions, improving performance in complex environments.
T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory
Our method surpasses the performance of existing state-of-the-art online learning methods in terms of both prediction accuracy and computational efficiency.
Improving Transferability for Cross-domain Trajectory Prediction via Neural Stochastic Differential Equation
To address this limitation, we propose a method based on continuous and stochastic representations of Neural Stochastic Differential Equations (NSDE) for alleviating discrepancies due to data acquisition strategy.
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