InhwanBae/DMRGCN
Official Code for "Disentangled Multi-Relational Graph Convolutional Network for Pedestrian Trajectory Prediction (AAAI 2021)"
This project helps predict the future paths of pedestrians in crowded environments, which is crucial for applications like autonomous vehicles or crowd management. It takes in past pedestrian movement data and outputs probable future trajectories, considering how people interact with each other. This tool is for researchers and engineers working on intelligent systems that need to understand and anticipate human movement patterns.
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Use this if you need to accurately predict pedestrian trajectories in complex, interactive scenarios while accounting for social dynamics and potential changes in direction.
Not ideal if you are looking for a simple, off-the-shelf solution for general object tracking or if your prediction needs do not involve understanding social interactions between multiple agents.
Stars
29
Forks
3
Language
Python
License
MIT
Category
Last pushed
Jul 16, 2025
Commits (30d)
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