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PaddleVideo

Update:

• add skeleton-base action recognition model CTR-GCN.
• add lite action recognition model MoViNet.
• add temporal segment model MS-TCN, ASRF.

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Introduction

PaddleVideo is a toolset for video tasks prepared for the industry and academia. This repository provides examples and best practice guildelines for exploring deep learning algorithm in the scene of video area.

Model and Applications

Model zoo

• Please refer to Installation guide and Usage doc before using the model zoo.

Dataset

Applications

Documentation tutorial

• AI-Studio Tutorial
  • [Official] Paddle 2.1 realizes video understanding optimization model -- PP-TSM
  • [Official] Paddle 2.1 realizes video understanding optimization model -- PP-TSN
  • [Official] Paddle 2.1 realizes the classic model of video understanding -- TSN
  • [Official] Paddle 2.1 realizes the classic model of video understanding -- TSM
  • BMN video action positioning
  • ST-GCN Tutorial for Figure Skate Skeleton Point Action Recognition
  • [Practice]video understanding transformer model TimeSformer
• Contribute code
  • How to add a new algorithm
  • Configuration system design analysis
  • How to mention PR

Competition

• Figure skating action recoginition using skeleton based on PaddlePaddle, AI Studio projects, video course
• Table tennis action proposal localization based on PaddlePaddle
• CCKS 2021: Knowledge Augmented Video Semantic Understanding

License

PaddleVideo is released under the Apache 2.0 license.

Thanks

• Many thanks to mohui37、zephyr-fun、voipchina for contributing the code for prediction.