ComplexVAD: Detecting Interaction Anomalies in Video
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917893962203136 |
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| author | Mumcu, Furkan Jones, Michael J. Yilmaz, Yasin Cherian, Anoop |
| author_facet | Mumcu, Furkan Jones, Michael J. Yilmaz, Yasin Cherian, Anoop |
| contents | Existing video anomaly detection datasets are inadequate for representing complex anomalies that occur due to the interactions between objects. The absence of complex anomalies in previous video anomaly detection datasets affects research by shifting the focus onto simple anomalies. To address this problem, we introduce a new large-scale dataset: ComplexVAD. In addition, we propose a novel method to detect complex anomalies via modeling the interactions between objects using a scene graph with spatio-temporal attributes. With our proposed method and two other state-of-the-art video anomaly detection methods, we obtain baseline scores on ComplexVAD and demonstrate that our new method outperforms existing works. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_09733 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ComplexVAD: Detecting Interaction Anomalies in Video Mumcu, Furkan Jones, Michael J. Yilmaz, Yasin Cherian, Anoop Computer Vision and Pattern Recognition Existing video anomaly detection datasets are inadequate for representing complex anomalies that occur due to the interactions between objects. The absence of complex anomalies in previous video anomaly detection datasets affects research by shifting the focus onto simple anomalies. To address this problem, we introduce a new large-scale dataset: ComplexVAD. In addition, we propose a novel method to detect complex anomalies via modeling the interactions between objects using a scene graph with spatio-temporal attributes. With our proposed method and two other state-of-the-art video anomaly detection methods, we obtain baseline scores on ComplexVAD and demonstrate that our new method outperforms existing works. |
| title | ComplexVAD: Detecting Interaction Anomalies in Video |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2501.09733 |