aleflabo/MoCoDAD
The official PyTorch implementation of the IEEE/CVF International Conference on Computer Vision (ICCV) '23 paper Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection.
This project helps security personnel or surveillance operators automatically detect unusual or suspicious activities in video footage. It takes recorded video data, processes the detected human movements (skeletons), and identifies actions that deviate from normal patterns, flagging them as potential anomalies. It is designed for those who monitor public spaces, workplaces, or restricted areas for safety and security.
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Use this if you need to automate the detection of unusual human behaviors in surveillance videos to improve security and response times.
Not ideal if you need to detect anomalies in videos without human subjects or if your primary focus is on object detection rather than human motion.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Aug 01, 2024
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