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Videomae Base Finetuned Kinetics Finetuned Fall Detect
A video action recognition model based on the VideoMAE architecture, specifically fine-tuned for fall detection tasks
Downloads 105
Release Time : 3/21/2024
Model Overview
This model is a video action recognition model fine-tuned for fall detection tasks based on the VideoMAE foundation model. It achieved 92.77% accuracy on the evaluation dataset.
Model Features
High Accuracy
Achieves 92.77% accuracy on fall detection tasks
Based on VideoMAE Architecture
Utilizes an efficient video masked autoencoder pre-training architecture
Lightweight Fine-tuning
Targeted fine-tuning on the foundation model while preserving original feature extraction capabilities
Model Capabilities
Video Action Recognition
Fall Detection
Human Behavior Analysis
Use Cases
Healthcare
Elderly Fall Monitoring
Used in nursing homes or home environments to monitor elderly falls
Can detect fall incidents in real-time and trigger alerts
Smart Surveillance
Public Space Safety Monitoring
Used for abnormal behavior detection in public spaces like shopping malls and hospitals
Can identify emergencies such as falls and notify security personnel
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