HMDB-AD, HMDB-Violence

本研究引入了两个新的数据集HMDB-AD和HMDB-Violence，旨在评估模型对复杂基于动作的异常检测能力。HMDB-AD包含995个视频片段，主要关注正常活动（如行走和跑步）与异常行为（如攀爬和翻筋斗）的区分。HMDB-Violence则是一个更大、更复杂的数据集，将16种动作类别分为7种暴力（异常）和9种非暴力（正常）活动，要求模型在更广泛的背景下分类事件。这两个数据集的创建是为了解决现有基准数据集在异常定义上的局限性，推动视频异常检测领域的研究进展。

This study introduces two novel datasets, HMDB-AD and HMDB-Violence, aimed at evaluating a model's capacity for complex action-based anomaly detection. HMDB-AD contains 995 video clips, focusing primarily on differentiating between normal activities (e.g., walking and running) and abnormal behaviors (e.g., climbing and somersaults). HMDB-Violence, on the other hand, is a larger and more complex dataset that categorizes 16 action classes into 7 violent (abnormal) and 9 non-violent (normal) activities, requiring models to classify events within a broader contextual framework. These two datasets were developed to address the limitations of existing benchmark datasets regarding anomaly definition, and to advance research progress in the field of video anomaly detection.