A probabilistic latent variable generative model learns to cluster social interactions directly from sequential trajectory observations without labels and uses the resulting patterns to improve pedestrian trajectory prediction.
Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting
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Learn to Quantify Social Interaction with Constraints for Pedestrian Walking
A probabilistic latent variable generative model learns to cluster social interactions directly from sequential trajectory observations without labels and uses the resulting patterns to improve pedestrian trajectory prediction.