HVU Dataset

HVU is organized hierarchically in a semantic taxonomy that focuses on multi-label and multi-task video understanding as a comprehensive problem that encompasses the recognition of multiple semantic aspects in the dynamic scene. HVU contains approx.~572k videos in total with 9 million annotations for training, validation, and test set spanning over 3142 labels. HVU encompasses semantic aspects defined on categories of scenes, objects, actions, events, attributes, and concepts which naturally captures the real-world scenarios.

HVU（Hierarchical Video Understanding）数据集采用层级语义分类体系进行组织，其核心聚焦于多标签和多任务视频理解，将其视为涵盖动态场景中多个语义方面识别的综合问题。HVU数据集总计包含约572,000个视频，并为训练、验证和测试集提供了9,000万个标注，覆盖3,142个标签。该数据集涵盖的场景、物体、动作、事件、属性和概念等语义方面，自然地捕捉了现实世界场景。