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Videomae Base Finetuned Accident Video Subset
This model is a fine-tuned version of MCG-NJU/videomae-base on a traffic accident video dataset, primarily designed for video classification tasks.
Downloads 98
Release Time : 11/6/2023
Model Overview
This is a video classification model based on the VideoMAE architecture, specifically fine-tuned for traffic accident videos, capable of identifying whether a video contains traffic accident scenes.
Model Features
Video Understanding Capability
Based on the VideoMAE architecture, it effectively understands video content.
Domain-Specific Optimization
Specifically fine-tuned for traffic accident scenarios.
Efficient Training
Utilizes linear learning rate scheduling and warm-up strategies to optimize the training process.
Model Capabilities
Video Classification
Traffic Accident Detection
Video Content Understanding
Use Cases
Traffic Safety
Automatic Traffic Accident Detection
Used in traffic monitoring systems to automatically identify accident video clips.
Achieved 58.06% accuracy on the test set.
Video Analysis
Video Content Classification
Classifies video content to identify whether it contains specific events.
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