This repository contains code for the AAAI 2021 paper:

A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization

Overview

Prerequisites

• PyTorch 1.7.1
• pytorch-lightning 1.1.2
• loguru, colorama, etc.

Older versions of PyTorch(1.3+) and pytorch-lightning(0.9+) should also work but not tested.

You can create a new conda environment with all the dependencies using:

conda env create -f environment.yml

How to Run

Download Data

The ground-truth and I3D features for THUMOS14 and ActivitiNet1.2 dataset can be downloaded from here:

Box Download Link

Please put the downloaded files/folders under data/ directory.

Training

To train HAM-Net on Thumos14 dataset:

python main.py

Please check options.py to know more about the available cli arguments.

Testing

To evaluate on Thumos14 dataset:

python main.py --test --ckpt [checkpoint_path]

For ActivityNet-1.2, use main_anet.py script.

Citation

If you find this repo useful for your research, please consider citing the paper:

@misc{islam2021hybrid,
      title={A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization}, 
      author={Ashraful Islam and Chengjiang Long and Richard J. Radke},
      year={2021},
      eprint={2101.00545},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Acknowledgement

• BaSNet
• ActivityNet
• WSAD