Forward and Backward Warping for Optical Flow-Based Frame Interpolation

Abstract

Frame interpolation methods generate intermediate frames by taking consecutive frames as inputs. This enables the generation of high frame rate videos from low frame rate videos. Recently, many deep learning-based frame interpolation methods have been proposed. One way of frame interpolation is by using the bi-directional optical flow. In many cases, these methods use backward warping to warp the input images to the desired frame. However, forward warping can also be used to warp the input frames. In this paper, we propose a frame interpolation method that utilizes both forward warping and backward warping. Experimental results show that utilizing both warping methods can enhance the performance compared to only using backward warping.