Dataset Hub

This dataset is used for recognizing the action of people climbing over fences, applicable to various security scenarios.

This dataset focuses on the automatic recognition of fighting and brawling behaviors to enhance security surveillance efficiency.

The Elderly Fall Detection Dataset focuses on monitoring elderly falls in the home environment to enhance family safety.

This dataset aims to recognize the usage of safety belts by workers during high-altitude operations.

This dataset is used to identify whether workers are wearing helmets and if they are wearing them correctly, supporting intelligent monitoring and safety management in the security field.

This dataset focuses on monitoring abnormal behavior of suspicious individuals in non-open areas.

This dataset is used for identifying dangerous climbing actions of children at home to enhance household safety protection.

This dataset is used to recognize the dangerous behaviors of pets, enhancing household security monitoring capabilities.

This dataset is used to identify abnormal searching behaviors in home environments to enhance the effectiveness of security surveillance.

This dataset is used to detect reverse movement on escalators, prolonged stay, and sitting on escalators, applicable to locations like subways and shopping malls.

This dataset is used to detect anomalous running and fleeing actions, aiding the intelligent upgrade of security monitoring systems.

A video dataset focused on action recognition of infants approaching dangerous areas.

This dataset focuses on the recognition of actions blocking the camera to enhance the intelligence level of security surveillance.

The Robbery and Coercion Action Recognition Dataset aims to help the security industry improve its ability to detect violent behavior.

This dataset is used for recognizing theft behavior in the commercial retail environment, suitable for the security industry.

This dataset is used to identify suspicious repeated glancing actions in surveillance scenes to enhance security monitoring effectiveness.

This dataset is dedicated to recognizing sudden falls of the elderly in non-exercise situations, applicable to various scenarios.