init

.gitignore

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+__pycache__/
+*.pyc
+*~
+*.pth

.style.yapf

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+[style]
+based_on_style: google
+column_limit: 160
+split_arguments_when_comma_terminated: true

.vscode/settings.json

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+{
+    "python.pythonPath": "/home/zhanbo/anaconda3/envs/ColorVid/bin/python"
+}

README.md

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+# Deep Exemplar-based Video Colorization (Pytorch Implementation)
+
+<img src='assets/teaser.png'/>
+
+### [Paper](https://arxiv.org/abs/1906.09909) | [Pretrained Model]() | [Youtube video](https://youtu.be/HXWR5h5vVYI)
+
+**Deep Exemplar-based Video Colorization, CVPR2019**
+
+[Bo Zhang](https://www.microsoft.com/en-us/research/people/zhanbo/)<sup>1,3</sup>,
+[Mingming He](http://mingminghe.com/)<sup>1,5</sup>,
+[Jing Liao](https://liaojing.github.io/html/)<sup>2</sup>,
+[Pedro V. Sander](https://www.cse.ust.hk/~psander/)<sup>1</sup>,
+[Lu Yuan](https://www.microsoft.com/en-us/research/people/luyuan/)<sup>4</sup>,
+[Amine Bermak](https://eebermak.home.ece.ust.hk/)<sup>1</sup>,
+[Dong Chen](https://www.microsoft.com/en-us/research/people/doch/)<sup>3</sup> <br>
+<sup>1</sup>Hong Kong University of Science and Technology,<sup>2</sup>City University of Hong Kong,
+<sup>3</sup>Microsoft Research Asia, <sup>4</sup>Microsoft Cloud&AI, <sup>5</sup>USC Institute for Creative Technologies
+
+## Prerequisites
+
+- Python 3.6+
+- Nvidia GPU + CUDA, CuDNN
+
+## Installation
+
+```bash
+conda create -n ColorVid python=3.6
+source activate ColorVid
+pip install -r requirements.txt
+```
+
+## Data preparation
+
+checkpoint, pre-trained vgg
+
+- input video frames
+- reference image
+- output
+
+## Test
+
+```bash
+python test.py
+```
+
+## TODO
+
+- [ ] Release the training code
+- [ ] Prepare the Colab Demo
+- [ ] Output the video
+- [ ] GIF teaser
+
+## Citation
+
+If you use this code for your research, please cite our paper.
+
+> @inproceedings{zhang2019deep,
+> title={Deep exemplar-based video colorization},
+> author={Zhang, Bo and He, Mingming and Liao, Jing and Sander, Pedro V and Yuan, Lu and Bermak, Amine and Chen, Dong},
+> booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
+> pages={8052--8061},
+> year={2019}
+> }
+
+## License
+
+This project is licensed under the MIT license.