Video Frame Interpolation without Temporal Priors (NeurIPS2020)
How to run
Prerequisites
- NVIDIA GPU + CUDA 9.0 + CuDNN 7.6.5
- Pytorch 1.1.0
First clone the project
git clone https://github.com/yjzhang96/UTI-VFI
cd UTI-VFI
mkdir pretrain_models
Download pretrained model weights from Google Drive. Put model weights "SEframe_net.pth" and "refine_net.pth" into directory "./pretrain_models"; put "model.ckpt" and "network-default.pytorch" into directory "./utils"
Dataset
download GoPro datasets with all the figh-frame-rate video frames from GOPRO_Large_all, and generate blurry videos for different exposure settings. You can generate the test datasets via run:
python utils/generate_blur.py
Test
After prepared test datasets, you can run test usding the following command:
sh run_test.sh
Note that to test the model on GOPRO datasets (datasets with groud-truth to compare), you need to set the argument "--test_type" to ''validation''. If you want to test the model on real-world video (without ground-truth), you need to use "real_world" instead.
Citation
@inproceedings{Zhang2019video,
title={Video Frame Interpolation without Temporal Priors},
author={Zhang, Youjian and Wang, Chaoyue and Tao, Dacheng},
journal={Advances in Neural Information Processing Systems},
year={2020}
}
Acknowledgment
Code of interpolation module borrows heavily from QVI
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