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Timesformer Hr Finetuned K600

Developed by fcakyon
TimeSformer is a video understanding model based on spatiotemporal attention mechanisms, with its high-resolution variant specifically fine-tuned for the Kinetics-600 dataset.
Downloads 22
Release Time : 12/10/2022

Model Overview

This model is primarily used for video classification tasks, supporting 600 category classifications in the Kinetics-600 dataset. It processes spatiotemporal video information using pure attention mechanisms without convolutional operations.

Model Features

Pure Attention Mechanism
Processes video data entirely based on Transformer architecture without traditional convolutional operations.
High-Resolution Support
A specially optimized high-resolution variant capable of handling more detailed video content.
Spatiotemporal Modeling
Simultaneously captures spatial and temporal dimensional information in videos.

Model Capabilities

Video Content Classification
Spatiotemporal Feature Extraction
Action Recognition

Use Cases

Video Analysis
Action Recognition
Identifies human actions and behaviors in videos.
Can recognize 600 action categories in the Kinetics-600 dataset.
Video Content Classification
Automatically classifies and tags video content.
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