V

Vit Base Violence Detection

Developed by jaranohaal
A violence detection model optimized based on the Vision Transformer (ViT) architecture, capable of classifying images into violent or non-violent scenes.
Downloads 2,140
Release Time : 6/19/2024

Model Overview

This model is based on google/vit-base-patch16-224-in21k and trained on real-life violence scene datasets, suitable for scenarios such as content moderation and video surveillance.

Model Features

High accuracy
Achieves a test accuracy of 98.80%, effectively identifying violent scenes.
Based on ViT architecture
Utilizes the Vision Transformer architecture, offering excellent image processing capabilities.
Trained on professional datasets
Trained on real-life violence scene datasets, ensuring recognition performance aligns with practical applications.

Model Capabilities

Image classification
Violence scene recognition
Content moderation

Use Cases

Security monitoring
Video surveillance system
Monitors video streams in real-time, automatically identifying violent behavior and triggering alerts.
Enhances monitoring efficiency and reduces manual review costs.
Content management
Social media content moderation
Automatically detects whether user-uploaded images or videos contain violent content.
Helps platforms quickly identify and handle non-compliant content.
Parental control
Child protection software
Filters images and videos containing violent content.
Protects children from exposure to harmful content.
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
Š 2025AIbase