This repository provides the implementation for video fast-forward with reinforcement learning, i.e. FFNet in our paper:
FFNet: Video Fast-Forwarding via Reinforcement Learning
If you find the codes or other related resources from this repository useful, please cite the following paper:
@inproceedings{lan2018ffnet,
title={FFNet: Video Fast-Forwarding via Reinforcement Learning},
author={Lan, Shuyue and Panda, Rameswar and Zhu, Qi and Roy-Chowdhury, Amit K},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
pages={6771--6780},
year={2018}
}
The original data we used in paper are available from the following websites
We offer a testing example with a pre-trained model in the ./model directory. Download this repository and run the following command:
python nn_test.py
The fast-forward result will be in the ./output directory.
If you want to train the model on your own data, you can find the script for training in nn_train.py. For more details, please refer to our paper.