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[논문 리뷰] STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive Applications STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive Applicationshttps://arxiv.org/abs/2503.07942 STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive ApplicationsThis paper presents a new method for anomaly detection in automated systems with time and compute sensitive requirements, such as autonomous driving, with unparalleled efficienc.. 더보기
[논문 리뷰] JOSENet: A Joint Stream Embedding Network for Violence Detection in Surveillance Videos JOSENet: A Joint Stream Embedding Network for Violence Detection in Surveillance Videoshttps://arxiv.org/abs/2405.02961 JOSENet: A Joint Stream Embedding Network for Violence Detection in Surveillance VideosThe increasing proliferation of video surveillance cameras and the escalating demand for crime prevention have intensified interest in the task of violence detection within the research commu.. 더보기
[논문 리뷰] VadCLIP: Adapting Vision-Language Models for Weakly SupervisedVideo Anomaly Detection VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detectionhttps://ojs.aaai.org/index.php/AAAI/article/view/28423 VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection | Proceedings of the AAAI Conferen ojs.aaai.orgWu, P., Zhou, X., Pang, G., Zhou, L., Yan, Q., Wang, P., & Zhang, Y. (2024, March). Vadclip: Adapting vision-language model.. 더보기

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