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Videomae Base Finetuned Ucf Crime2
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Videomae Base Finetuned Ucf Crime2

Developed by shazab
A video analysis model based on the VideoMAE base model fine-tuned on the UCF-Crime dataset for abnormal behavior detection
Video Processing
Transformers
#Video Anomaly Detection#Criminal Behavior Recognition#Semi-Supervised Learning
Downloads 16
Release Time : 5/30/2023

Model Overview

This model is a video understanding model based on the VideoMAE architecture, specifically optimized for crime scene detection tasks, capable of analyzing video content and identifying abnormal behaviors

Model Features

Video Anomaly Detection
Video understanding capabilities specifically optimized for crime scenes and abnormal behavior detection
Self-Supervised Pre-training
Utilizes VideoMAE's self-supervised pre-training method to learn effective video representations
Efficient Fine-tuning
Precisely fine-tuned on specific tasks to balance computational efficiency and detection accuracy

Model Capabilities

Video Content Analysis
Abnormal Behavior Recognition
Crime Scene Detection

Use Cases

Public Safety
Surveillance Video Analysis
Automatically analyzes abnormal behaviors in surveillance videos
Achieves an accuracy of 0.52 on the validation set
Intelligent Security System
Integrated into security systems for real-time detection of suspicious activities
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