Corpus ID: 220793224

Dynamic Relational Inference in Multi-Agent Trajectories

@article{Xiao2020DynamicRI,
  title={Dynamic Relational Inference in Multi-Agent Trajectories},
  author={Ruichao Xiao and R. Yu},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.13524}
}

Ruichao Xiao, R. Yu

Published 2020

Computer Science, Mathematics

ArXiv

Inferring interactions from multi-agent trajectories has broad applications in physics, vision and robotics. Neural relational inference (NRI) is a deep generative model that can reason about relations in complex dynamics without supervision. In this paper, we take a careful look at this approach for relational inference in multi-agent trajectories. First, we discover that NRI can be fundamentally limited without sufficient long-term observations. Its ability to accurately infer interactions… CONTINUE READING

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