allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories. We
present a unified model architecture for simultaneous agent future heatmap estimation, in
which we leverage hierarchical and sparse image generation for fast and memory-efficient
inference. We propose a learnable trajectory recombination model that takes as input a set
of predicted trajectories for each agent and outputs its consistent reordered recombination …