vita-epfl/social-nce
[ICCV] Social NCE: Contrastive Learning of Socially-aware Motion Representations
This project helps improve how robots and autonomous vehicles navigate safely through crowded spaces. It takes observed trajectories of people or objects and produces a model that predicts future movements, significantly reducing the likelihood of collisions. This is ideal for roboticists, autonomous vehicle engineers, or anyone developing systems that operate in close proximity to humans or other dynamic obstacles.
166 stars. No commits in the last 6 months.
Use this if you need to train robust motion models for autonomous agents that can predict and avoid collisions in dense, dynamic environments.
Not ideal if your application doesn't involve motion forecasting in crowded or interactive settings.
Stars
166
Forks
25
Language
Python
License
BSD-2-Clause
Category
Last pushed
Jul 10, 2022
Commits (30d)
0
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