InhwanBae/NPSN
Official Code for "Non-Probability Sampling Network for Stochastic Human Trajectory Prediction (CVPR 2022)"
This project helps improve the accuracy and reliability of predicting where people will move next, given their past movements. It takes existing trajectory prediction models and refines their output to show more realistic and diverse possible paths. This is ideal for researchers or practitioners working on human motion forecasting in fields like robotics, autonomous driving, or crowd management.
No commits in the last 6 months.
Use this if you are developing or evaluating systems that need to accurately forecast multiple possible human trajectories and want to improve the quality of those predictions.
Not ideal if you are looking for a complete, production-ready application for real-time deployment without further development.
Stars
73
Forks
12
Language
Python
License
MIT
Category
Last pushed
Jul 16, 2025
Commits (30d)
0
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