• Corpus ID: 238744427

THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling

@article{Gilles2021THOMASTH,
  title={THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling},
  author={Thomas Gilles and Stefano Sabatini and Dzmitry V. Tsishkou and Bogdan Stanciulescu and Fabien Moutarde},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.06607}
}
In this paper, we propose THOMAS, a joint multi-agent trajectory prediction framework allowing for efficient and consistent prediction of multi-agent multimodal trajectories. We present a unified model architecture for fast and simultaneous agent future heatmap estimation leveraging hierarchical and sparse image generation. We demonstrate that heatmap output enables a higher level of control on the predicted trajectories compared to vanilla multi-modal trajectory regression, allowing to… 

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