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Learning-to-Extract-Flawless-Slow-Motion-from-Blurry-Videos

This repository is a PyTorch implementation of the paper "Learning to Extract Flawless Slow Motion from Blurry Videos" from CVPR 2019 [paper][full version][video]

If you find our work useful in your research or publication, please cite our work:

@InProceedings{Jin_2019_CVPR,
author = {Jin, Meiguang and Hu, Zhe and Favaro, Paolo},
title = {Learning to Extract Flawless Slow Motion from Blurry Videos},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}

Requirements

This code has been tested with Python 3.7 and Pytorch 1.1.0.

Test

Unzip a real test video and download the pretrained model (cvpr19_model.pth) from google drive. This script will generate a 10x slow motion video.

unzip test_video_01.zip
python test_demo.py --cuda --model cvpr19_model.pth --input test_video_01 --out result

Dataset

You can find the sony slow motion video dataset used in the training from the following link.

Training

To be updated

Contact

If you have any suggestions and questions, please send an email to jinmeiguang@gmail.com