SuperSlowMo
PythonML pipeline to create super slow motion using frame interpolation
An implementation of video frame interpolation as described in the wildy popular research of Jing Et al. using an end-to-end convolutional neural network for generating spatially and temporally coherent video sequences
The main idea is to compute bi-directional optical flows from two frames using a U-Net architecture and combining them to approximate immediate flows
The data was trained on the adobe240fps dataset