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Timesformer Base Finetuned K600

Developed by onnx-community
TimeSformer is a video understanding model based on the Transformer architecture, specifically designed for video classification tasks.
Downloads 16
Release Time : 8/9/2024

Model Overview

This model is a video classification model based on the Transformer architecture, fine-tuned on the Kinetics-600 dataset, suitable for video action recognition tasks.

Model Features

Transformer-based Video Understanding
Utilizes the Transformer architecture to process video sequences, effectively capturing spatiotemporal features.
Kinetics-600 Fine-tuning
Fine-tuned on the large-scale video dataset Kinetics-600, demonstrating strong video action recognition capabilities.
ONNX Compatibility
Provides ONNX format weights, facilitating deployment on web platforms using Transformers.js.

Model Capabilities

Video Classification
Action Recognition
Spatiotemporal Feature Extraction

Use Cases

Video Analysis
Action Recognition
Identifies the types of actions performed by individuals in videos, such as running, dancing, etc.
Behavior Analysis
Analyzes behavioral patterns in videos for applications like surveillance or sports analysis.
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