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Test With Sdfvd
A video understanding model fine-tuned based on MCG-NJU/videomae-base, with average performance on the evaluation set (accuracy 50%)
Downloads 16
Release Time : 4/21/2025
Model Overview
This model is a video classification model based on the VideoMAE architecture, suitable for video content analysis tasks. Specific applications require further confirmation
Model Features
Video Feature Extraction
Based on the VideoMAE architecture, excels at extracting spatiotemporal features from video sequences
Transfer Learning Capability
Fine-tuned on the base model, suitable for specific video classification tasks
Model Capabilities
Video Content Analysis
Video Classification
Use Cases
Video Understanding
Video Classification
Classify and recognize video content
Current accuracy 50%
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