Studio Dataset for Self-harm Detection

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

本数据集为自残（self-harm）数据集，由ZIOVISION有限公司（ZIOVISION Co. Ltd.）开发。数据集共包含1120段视频，通过聘请演员模拟自残行为，并布设四台摄像机录制场景，以实现无死角全面覆盖。本数据集收录的自残行为仅限针对特定身体部位的‘切割’动作，指定自残区域包括手腕、前臂及大腿。完整数据集可通过https://github.com/zv-ai/ZV_Self-harm-Dataset.git 获取。

搜集汇总

背景与挑战

背景概述

Studio Dataset for Self-harm Detection是一个用于自残检测的视频数据集，包含1,120个由演员模拟的自残行为视频，专注于'切割'动作，覆盖手腕、前臂和大腿区域。该数据集由ZIOVISION Co. Ltd.开发，采用多摄像头录制以确保无盲点，并附带XML注释文件，适用于人工智能、医学影像和计算机视觉领域的研究。