HAMF feeds learnable future motion tokens into the scene encoder alongside road and agent tokens, then uses a Mamba decoder to output six diverse trajectories, achieving competitive Argoverse 2 results with 3.0M parameters.
Simpl: A simple and efficient multi-agent motion prediction baseline for autonomous driving,
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HAMF: A Hybrid Attention-Mamba Framework for Joint Scene Context Understanding and Future Motion Representation Learning
HAMF feeds learnable future motion tokens into the scene encoder alongside road and agent tokens, then uses a Mamba decoder to output six diverse trajectories, achieving competitive Argoverse 2 results with 3.0M parameters.