tnquang1416 / FI-DUSGAN

Implementation for Video Frame Interpolation Via Down-Up Scale Generative Adversarial Networks (2022).

FI-DUSGAN

This is the official implementation for Video Frame Interpolation Via Down-Up Scale Generative Adversarial Networks (2022).

Requirements

For using this implementation, we recommend PyTorch with version 1.5.0 or later.

Dataset

The target dataset of this implementation is the Vimeo-90k dataset. The sample data directory is organized following the frame interpolation subset of the Vimeo90k.

Please see the Vimeo-90k dataset documentation for more details.

Run the code

python train.py --path=cpt_folder

Pre-trained model

Please find it on Google Drive and then put in the pre-trained folder. Note that rename the file to "net_gen.pt" might be required.

Reference

@ARTICLE{9097443,
  author={Tran, Quang Nhat and Yang, Shih-Hsuan},
  journal={Computer Vision and Image Understanding}, 
  title={Video Frame Interpolation Via Down-Up Scale Generative Adversarial Networks}, 
  year={2022},
  volume={220},
  doi={https://doi.org/10.1016/j.cviu.2022.103434}}