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
- CUDA 9.0
Make a directory ./data for saving models and a directory ./pretrained for pretrained models.
- The pretrained SEENet Model can be downloaded from https://www.dropbox.com/sh/m4jrus3x7cjyh9t/AADxVp06scNlQDWLsVTHXHD1a?dl=0
- The preprocessed KTH dataset can be downloaded from https://www.dropbox.com/sh/5wv2m9ov0usnikj/AAC6Fo3HMPIlXLho6pZKmNtUa?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 --test False
To train predict part:
python3 ./src/main.py --train_feature False --test 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:
ArXiv Version:
@article{wang2019order,
title={Order Matters: Shuffling Sequence Generation for Video Prediction},
author={Wang, Junyan and Hu, Bingzhang and Long, Yang and Guan, Yu},
journal={arXiv preprint arXiv:1907.08845},
year={2019}
}