The Tensorflow implementation of "Order Matters: Shuffling Sequence Generation for Video Prediction" (BMVC2019) by Junyan Wang, Bingzhang Hu, Yang Long, Yu Guan.
- Python: 3.6.8
- Tensorflow: 1.12.0
(The proprecessed dataset will provide later)
Make a directory ./data for saving models and a directory ./pretrained for saving logs.
- The pretrained SEENet Model can be downloaded from https://www.dropbox.com/sh/m4jrus3x7cjyh9t/AADxVp06scNlQDWLsVTHXHD1a?dl=0
Make a directory ./models for saving models and a directory ./logs for saving logs.
To train motion and content features:
python3 ./src/main.py --train_feature True
To train predict part:
python3 ./src/main.py --train_feature False
The predicted samples can be seen in ./samples folder. The detailed arguments can be set up in ./src/args.py
python3 ./src/main.py --test True
The test predicted samples can be seen in ./samples/test folder
If you use this code or reference our paper in your work please cite this publication as:
@misc{wang2019order,
title={Order Matters: Shuffling Sequence Generation for Video Prediction},
author={Junyan Wang and Bingzhang Hu and Yang Long and Yu Guan},
year={2019},
eprint={1907.08845},
archivePrefix={arXiv},
primaryClass={cs.CV}
}