InhwanBae/Crowd-Behavior-Generation

Official Code for "Continuous Locomotive Crowd Behavior Generation (CVPR 2025)"

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Combines a diffusion-based crowd emitter with a state-switching simulator to generate lifelong agent trajectories from single scene images, eliminating dependency on observation sequences. Trained on ETH, UCY, SDD, and EDIN datasets with PyTorch 2.2.2, it supports both synthetic and real-world scenarios via Sim2Real/Real2Sim evaluation, plus 3D visualization through CARLA integration for interactive scene population and behavior customization.

No Package No Dependents
Maintenance 6 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 16 / 25

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Stars

44

Forks

8

Language

Python

License

MIT

Last pushed

Nov 07, 2025

Commits (30d)

0

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