EARL
This repository provides a simple implementation of the work “Efficient Sparse Attacks on Videos using Reinforcement Learning”
Example:
Demo:
Here, we provide 5 video clips in folder “dataset_numpy”, you can run the following script and observe the effect:
python un_attack_show.py # untargeted attack
or
python T_attack_show.py # targeted attack
Threat models:
The video classification model, please refer to project https://github.com/FenHua/action-recognition
You can train the recognition model with your own data, and use the video attack method to attack them.
Please cite:
It will be added soon!
