ChuhuaW/SGNet.pytorch

Pytorch Implementation for Stepwise Goal-Driven Networks for Trajectory Prediction (RA-L/ICRA2022)

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This project helps predict the future movements of pedestrians or vehicles in various environments. It takes in existing trajectory data (e.g., from surveillance cameras or sensor feeds) and outputs likely future paths. This is useful for researchers and engineers working on autonomous systems or human behavior modeling who need to forecast movement accurately.

125 stars. No commits in the last 6 months.

Use this if you are a researcher or engineer in robotics or autonomous driving and need to train or evaluate models for predicting pedestrian or vehicle trajectories.

Not ideal if you are a practitioner looking for an off-the-shelf solution for real-time deployment without expertise in machine learning model training and evaluation.

autonomous-driving robotics pedestrian-behavior-prediction vehicle-trajectory-forecasting computer-vision-research

No License Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 10 / 25

Maturity 8 / 25

Community 16 / 25

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125

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Language

Python

License

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