daniel-code/TubeViT
An unofficial implementation of TubeViT in "Rethinking Video ViTs: Sparse Video Tubes for Joint Image and Video Learning"
This project helps researchers and developers working with video data to efficiently train and evaluate models for video understanding tasks. You provide a dataset of video clips, and it produces a trained model capable of classifying the actions or content within those videos. This is designed for machine learning practitioners focused on video analysis.
No commits in the last 6 months.
Use this if you need to train a video classification model on a custom dataset, especially if you're exploring the TubeViT architecture for action recognition.
Not ideal if you're looking for a simple tool to analyze videos without any machine learning setup or if you require an out-of-the-box inference solution without training.
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94
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9
Language
Python
License
MIT
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Last pushed
Sep 13, 2024
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