Future Motion Estimation for Video Frame Extrapolation

Seunggyun Woo, Junheum Park, Chang-Su Kim

Abstract: We propose a novel video frame extrapolation algorithm based on future motion estimation. First, we estimate optical flows between a pair of input frames and predict future motions using two schemes: motion doubling and motion mirroring. Then, we forward warp the input frames by employing the two kinds of predicted motion fields, respectively. Finally, we develop a synthesis network to generate a future frame from the warped frames. Experimental results show that the proposed algorithm outperforms recent video frame extrapolation algorithms on various datasets.