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IONet

This repo is the implementation of paper Weakly-Supervised Action Localization via Embedding-Modeling Iterative Optimization.

Recommended Environment

  • Ubuntu 16.04.6
  • Python 3.6
  • Cuda 9.0
  • PyTorch 1.1.0

Prerequisites

  • Install dependencies: pip install -r requirements.txt.
  • Prepare THUMOS14 and ActivityNet datasets.

Feature Extraction

We employ I3D features in the paper.

We recommend to extract the features using the followingf repo:

Run

  1. For training the model:
python train.py
  1. For testing the model:
python test.py

The final results are saved in .npz format.

Citation

Contact

If you have any questions, please contact me (shihaichao@iie.ac.cn).

License

MIT

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