Prevent-Jack fuses six local behaviors into a context steering framework for swarms of heavy articulated vehicles, delivering collision and jackknifing avoidance at the expense of deadlocks and livelocks observed in 15,000 simulations.
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A coarse-to-fine autoregressive framework with multi-scale tokenization and scale-aware control reconstructs human motion from sparse observations and reports SOTA accuracy on AMASS.
citing papers explorer
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PREVENT-JACK: Context Steering for Swarms of Long Heavy Articulated Vehicles
Prevent-Jack fuses six local behaviors into a context steering framework for swarms of heavy articulated vehicles, delivering collision and jackknifing avoidance at the expense of deadlocks and livelocks observed in 15,000 simulations.
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MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observations
A coarse-to-fine autoregressive framework with multi-scale tokenization and scale-aware control reconstructs human motion from sparse observations and reports SOTA accuracy on AMASS.