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+# pytorch-sepconv
+This is a reference implementation of Video Frame Interpolation via Adaptive Separable Convolution [1] using PyTorch. Given two frames, it will make use of <a href="http://graphics.cs.pdx.edu/project/adaconv">adaptive convolution</a> [2] in a separable manner to interpolate the intermediate frame. Should you be making use of our work, please cite our paper [1].
+
+<a href="https://arxiv.org/abs/1703.07514" rel="Paper"><img src="http://content.sniklaus.com/SepConv/Paper.jpg" alt="Paper" width="100%"></a>
+
+For the Torch version of this work, please see: https://github.com/sniklaus/torch-sepconv
+
+## setup
+To build the implementation and download the pretrained networks, run `bash install.bash` and make sure that you configured the `CUDA_HOME` environment variable. After successfully completeing this step, run `python run.py` to test it. Should you receive an error message regarding an invalid device function during execution, configure the utilized CUDA architecture within `install.bash` to something your graphics card supports.
+
+## usage
+To run it on your own pair of frames, use the following command. You can either select the `l1` or the `lf` model, please see our paper for more details.
+
+```
+python run.py --model lf --first ./images/first.png --second ./images/second.png --out ./result.png
+```
+
+## video
+<a href="http://web.cecs.pdx.edu/~fliu/project/sepconv/demo.mp4" rel="Video"><img src="http://web.cecs.pdx.edu/~fliu/project/sepconv/screen.jpg" alt="Video" width="100%"></a>
+
+## license
+The provided implementation is strictly for academic purposes only. Should you be interested in using our intelectual property, please feel free to contact us.
+
+## references
+```
+[1]  @inproceedings{Niklaus_ICCV_2017,
+         author = {Simon Niklaus and Long Mai and Feng Liu},
+         title = {Video Frame Interpolation via Adaptive Separable Convolution},
+         booktitle = {IEEE International Conference on Computer Vision},
+         year = {2017}
+     }
+```
+
+```
+[2]  @inproceedings{Niklaus_CVPR_2017,
+         author = {Simon Niklaus and Long Mai and Feng Liu},
+         title = {Video Frame Interpolation via Adaptive Convolution},
+         booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
+         year = {2017}
+     }
+```
+
+## acknowledgment
+This work was supported by NSF IIS-1321119. This video uses materials under a Creative Common license or with the owner's permission, as detailed at the end.
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