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cs.CV2026
ESOM: Efficiently Understanding Streaming Video Anomalies with Open-world Dynamic Definitions
Zihao Liu, Xiaoyu Wu, Wenna Li +2
Open-world video anomaly detection (OWVAD) aims to detect and explain abnormal events under different anomaly definitions, which is important for applications such as intelligent s…
cs.CV2025
VQualA 2025 Challenge on Engagement Prediction for Short Videos: Methods and Results
Dasong Li, Sizhuo Ma, Hang Hua +40
This paper presents an overview of the VQualA 2025 Challenge on Engagement Prediction for Short Videos, held in conjunction with ICCV 2025. The challenge focuses on understanding a…
cs.CV2025
Language-guided Open-world Video Anomaly Detection under Weak Supervision
Zihao Liu, Xiaoyu Wu, Jianqin Wu +2
Video anomaly detection (VAD) aims to detect anomalies that deviate from what is expected. In open-world scenarios, the expected events may change as requirements change. For examp…