InhwanBae/GraphTERN
Official Code for "A Set of Control Points Conditioned Pedestrian Trajectory Prediction (AAAI 2023)"
This project helps predict the future movements of pedestrians, which is crucial for applications like autonomous vehicles or crowd management. It takes in past pedestrian movement data and outputs refined, likely future paths, considering multiple possibilities. City planners, event organizers, or autonomous system developers would find this tool beneficial.
No commits in the last 6 months.
Use this if you need to accurately forecast pedestrian paths to prevent collisions, optimize crowd flow, or enhance safety in dynamic environments.
Not ideal if you are looking to predict the movement of non-pedestrian objects or require real-time, ultra-low-latency predictions for mission-critical systems without any prediction refinement.
Stars
49
Forks
4
Language
Python
License
MIT
Category
Last pushed
Jul 16, 2025
Commits (30d)
0
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