agrimgupta92/sgan
Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018
This project helps researchers and developers working with robotics, autonomous vehicles, or surveillance to predict how people will move in a scene. It takes observed human movement trajectories as input and generates multiple socially acceptable future paths for each person. This is ideal for those who need to simulate or anticipate human behavior in dynamic environments.
905 stars. No commits in the last 6 months.
Use this if you need to predict socially aware human movement in complex, multi-person scenarios.
Not ideal if your application requires predicting the movement of non-human entities or does not involve social interaction.
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905
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272
Language
Python
License
MIT
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Last pushed
Nov 24, 2023
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