Jun 11, 2020 · Artificial Intelligence

Pedestrian Trajectory Prediction: Methodology and Experience from the ICRA 2020 TrajNet++ Competition

The ICRA 2020 TrajNet++ competition challenged teams to predict 4.8‑second pedestrian paths from 3.6‑second observations, and Meituan’s winning solution used a Seq2Seq world‑model that encodes past trajectories, updates a spatio‑temporal interaction map, and decodes future positions, achieving a 1.24 m final displacement error and demonstrating readiness for real‑world unmanned delivery.

AIICRA 2020Prediction

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Pedestrian Trajectory Prediction: Methodology and Experience from the ICRA 2020 TrajNet++ Competition

Meituan Technology Team

Nov 21, 2019 · Artificial Intelligence

StarNet: Global Interaction Network for Pedestrian Trajectory Prediction

StarNet is a neural network for pedestrian trajectory prediction in large‑scale delivery, using a global dynamic map and a Hub‑Host architecture to model interactions efficiently, reducing complexity from O(N²) to O(N), and achieving higher accuracy with fast inference compared to baseline methods.

Deep LearningLSTMPrediction

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StarNet: Global Interaction Network for Pedestrian Trajectory Prediction