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Timesformer Base Finetuned Ssv2
TimeSformer is a Transformer-based video understanding model specifically optimized for temporal action recognition tasks.
Downloads 17
Release Time : 8/9/2024
Model Overview
This model is a variant of the TimeSformer architecture developed by Facebook, fine-tuned specifically on the Something-Something V2 dataset, suitable for video action recognition tasks.
Model Features
Spatiotemporal Attention Mechanism
Utilizes Transformer architecture to process both spatial and temporal dimensions, effectively capturing spatiotemporal features in videos.
Efficient Video Processing
Compared to traditional 3D CNN models, it can process long video sequences more efficiently.
ONNX Compatibility
Provides ONNX format weights for easy deployment in web environments.
Model Capabilities
Video Action Recognition
Temporal Behavior Understanding
Video Content Analysis
Use Cases
Intelligent Video Analysis
Action Recognition System
Recognizes human actions and behaviors in videos
Can accurately classify 174 types of actions in the Something-Something V2 dataset.
Video Content Understanding
Analyzes video content and extracts key action information
Human-Computer Interaction
Gesture Recognition
Recognizes human gestures and actions in videos
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