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Timesformer Base Finetuned K400

Developed by onnx-community
TimeSformer is a Transformer-based video understanding model, specifically fine-tuned on the Kinetics-400 dataset.
Downloads 17
Release Time : 8/9/2024

Model Overview

TimeSformer is a Transformer model for video classification, efficiently processing video data by decoupling spatial and temporal attention. This version is fine-tuned on the Kinetics-400 dataset with ONNX weights, suitable for web deployment.

Model Features

Efficient Video Processing
Utilizes decoupled spatial and temporal attention mechanisms for effective video data processing.
Web-Compatible
Provides ONNX weights version, capable of running on web browsers via Transformers.js.
Pre-trained Fine-tuning
Fine-tuned on the Kinetics-400 dataset, suitable for video classification tasks.

Model Capabilities

Video Classification
Video Content Understanding
Action Recognition

Use Cases

Video Analysis
Action Recognition
Identify human actions and behaviors in videos.
Accurately classifies 400 action categories in the Kinetics-400 dataset.
Content Moderation
Automatically detect inappropriate content in videos.
Smart Surveillance
Abnormal Behavior Detection
Monitor abnormal behavior patterns in surveillance videos.
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