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Videomae Base Finetuned Ucfcrime Full

Developed by archit11
A video classification model fine-tuned on the UCF-CRIME dataset based on the VideoMAE framework, focusing on vandalism detection
Downloads 85
Release Time : 3/17/2024

Model Overview

This model is a fine-tuned version of MCG-NJU/videomae-base on the UCF-CRIME dataset, primarily used for vandalism detection and classification tasks in videos.

Model Features

Vandalism Detection
Specifically designed to recognize and classify vandalism in videos
Based on VideoMAE Framework
Utilizes the efficient VideoMAE self-supervised learning framework for pre-training
Fine-tuned on UCF-CRIME Dataset
Fine-tuned on the publicly available UCF-CRIME dataset, focusing on abnormal behavior recognition

Model Capabilities

Video Classification
Vandalism Detection
Real-time Video Analysis

Use Cases

Security Monitoring
Public Area Anomaly Detection
Detects vandalism or abnormal activities in public areas
Smart Home
Home Security Monitoring
Detects potential vandalism through home cameras
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