Package Theft Detection from Smart Home Security Cameras
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Abstract (arXiv)
Package theft detection has been a challenging task mainly due to lack of training data and a wide variety of package theft cases in reality. In this paper, we propose a new Global and Local Fusion Package Theft Detection Embedding (GLF-PTDE) framework to generate package theft scores for each segment within a video to fulfill the real-world requirements on package theft detection. Moreover, we construct a novel Package Theft Detection dataset to facilitate the research on this task. Our method achieves 80% AUC performance on the newly proposed dataset, showing the effectiveness of the proposed GLF-PTDE framework and its robustness in different real scenes for package theft detection.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 6 references that are in the map. First posted on arXiv 24 May 2022.
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References · 2
- 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,162
- 2018Real-world Anomaly Detection in Surveillance Videoscited by 577
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