ee5053's Introduction

Computer Vision Project for Frame Interpolation

This is the project content of frame interpolation. Now we are implementing the paper Softmax Splatting for Video Frame Interpolation [1]. We'll try various techniques to improve the quality of output frames.

setup

The following packages need to be installed:

pip install cupy-cuda101 if your cuda version is v10.1, please use the version corresponding to your cuda version

pip install opencv-contrib-python

pip install torch

pip install tensorflow if version is higher than 1.15, it may fails.

usage

Before generating frames, you need to check whether the flow files exist. If not, you can cd PWCNet, and then execute python predict.py --task type_of_task. After that, the frames are generated by execute python main.py --task type_of_task. Finally, you can simply execute bash eval.sh to check the quality of generated frames.

references

[1]  @inproceedings{Niklaus_CVPR_2020,
         author = {Simon Niklaus and Feng Liu},
         title = {Softmax Splatting for Video Frame Interpolation},
         booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
         year = {2020}
     }

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