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| author | sniklaus <simon.niklaus@outlook.com> | 2017-11-24 14:51:29 -0800 |
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| committer | sniklaus <simon.niklaus@outlook.com> | 2017-11-24 14:51:29 -0800 |
| commit | dccd8e53c668a532792d46302caec7419de6e2be (patch) | |
| tree | 30875e9f10ed6a8c33449bb6f24cedbc0843bfac /README.md | |
| parent | cfd6a91a628c603eeeecf517340ac0474a126496 (diff) | |
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| -rw-r--r-- | README.md | 1 |
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@@ -4,6 +4,7 @@ This is a reference implementation of Video Frame Interpolation via Adaptive Sep <a href="https://arxiv.org/abs/1708.01692" 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 +For a third-party fork with video support, consider: https://github.com/dagf2101/pytorch-sepconv ## setup To build the implementation and download the pre-trained networks, run `bash install.bash` and make sure that you configured the `CUDA_HOME` environment variable. After successfully completing 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. |