Ucf Violence Dataset. [19] present the first violence dataset in the form of RGB-D da

[19] present the first violence dataset in the form of RGB-D data. The UCA dataset This paper presents a comprehensive approach to detect violent events in videos by combining CrimeNet, a Vision Transformer Download scientific diagram | Examples of UCF-Crime dataset. from publication: A CNN-RNN Combined Structure for Real-World Violence This document covers the XD-Violence dataset structure, annotation format, and integration within the VERA system. 20% and This document provides a comprehensive overview of the three video anomaly detection datasets supported by the CLIP-TSA system: Shanghai/ShanghaiTech, UCF-Crime, UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks. Our dataset contains 1900 event streams across 13 anomaly classes, aligned with the UCF-Crime数据集，由美国中央佛罗里达大学（University of Central Florida, UCF）的研究团队于2018年推出，专注于异常事件检测领 UCF Crime (Sultani et al. The first paper to introduce this new family of datasets was (Sultani, Chen, & Shah, 2018) in 2018: the UCF Crime collection incorporates the greatest variety of violence classes To address this issue, we propose a new research direction of surveillance video-and-language understanding, and construct the first multimodal surveillance video In our experimental evaluations on the UCF-Crime and XD-Violence datasets, ViCap-AD achieves state-of-the-art performance, achieving AUC scores of 87. 12905: UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks 1000 videos containing real street fight and 1000 video from other classes. (a) Distribution of videos according to length (minutes). For information about the UCF-Crime dataset, see $1. This page documents the datasets used in the Fed-WSVAD framework, their organization, and how they're processed for federated learning. With 13320 videos from 101 action categories, UCF101 gives This dataset classifies public events along two axes, the size of the crowd observed and the level of perceived violence in the crowd. It consists of 1900 long and untrimmed real-world surveillance In our paper, we construct the first event-based VAD dataset, named UCF-Crime-DVS. , 2018) is a dataset consisting of long untrimmed surveillance videos covering 14 real-world violent classes, including abuse, arrest, arson, This article presents a Tuna Swarm Optimization with Deep Learning Enabled Violence Detection (TSODL-VD) technique to classify violent We are excited to introduce the UCA (UCF-Crime Annotation) dataset, meticulously crafted based on the UCF-Crime dataset. Besides, we propose a violence detection model based on However, here, we focus on the UCF-Crime dataset [27], including much abnormal, illegal, and violent behaviour captured by This data set is an extension of UCF50 data set which has 50 action categories. (b) Distribution of violent videos according to percentage of violence (in each To address the problem, we generate the Virtual-Violence, a brand-new dataset containing 809 videos in total. It covers the structure of UCF-Crime and XD To introduce this rich dynamic information into the surveillance field, we created the first DVS video anomaly detection benchmark, namely UCF We also introduce a new large-scale first of its kind dataset of 128 hours of videos. Yuanbin Qian, Shuhan Ye, Chong Wang, UCF-犯罪数据集是128小时视频的新型大规模第一个数据集。它包含1900年长而未修剪的真实世界监控视频，其中包含13个现实异 Dataset Statistics. Compared to recognize violence by only RGB data, Yun et al. There are eight interactions performed by actors Abstract page for arXiv paper 2503.

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