Psychic-DL/DiffTAD

DiffTAD: Denoising Diffusion Probabilistic Models for Vehicle Trajectory Anomaly Detection

29
/ 100
Experimental

This project helps identify unusual vehicle movements in traffic video surveillance, autonomous driving, or taxi services. It takes raw vehicle trajectory data, processes it, and outputs flags for anomalous paths without requiring manual labeling. This tool is for traffic analysts, autonomous vehicle developers, and urban planning specialists concerned with vehicle behavior and safety.

No commits in the last 6 months.

Use this if you need to automatically detect abnormal vehicle trajectories efficiently and accurately from large datasets, without the time and cost of manual data annotation.

Not ideal if your anomaly detection needs are outside of vehicle trajectories or if you prefer traditional, rule-based anomaly detection systems.

traffic-monitoring autonomous-driving fleet-management urban-planning fraud-detection
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

33

Forks

2

Language

Python

License

MIT

Last pushed

Nov 28, 2023

Commits (30d)

0

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