Action recognition

This Dataset is a self-harm dataset developed by ZIOVISION Co. Ltd. It consists of 1,120 videos. Actors were hired to simulate self-harm behaviors, and the scenes were recorded using four cameras to ensure full coverage without blind spots. Self-harm behaviors in the dataset are limited to "cutting" actions targeting specific body parts. The designated self-harm areas include the wrists, forearms, and thighs.

 The full dataset can be accesssed through https://github.com/zv-ai/ZV_Self-harm-Dataset.git

Most of the existing human action datasets are common human actions in daily scenes（e.g. NTU RGB+D series, Kinetics series）, not created for Human-Robot Interaction(HRI), and most of them are not collected based on the perspective of the service robot, which can not meet the needs of vision-based interactive action recognition.

This dataset is named as “Human-Robot Interactive Action Dataset From The Perspective Of Service Robot (THU-HRIA dataset) “ ,which is created for indoor service robot action interaction, collected by Tsinghua University.