  In this paper, we propose an algorithm to interpolate between a pair of
images of a dynamic scene. While in the past years significant progress in
frame interpolation has been made, current approaches are not able to handle
images with brightness and illumination changes, which are common even when the
images are captured shortly apart. We propose to address this problem by taking
advantage of the existing optical flow methods that are highly robust to the
variations in the illumination. Specifically, using the bidirectional flows
estimated using an existing pre-trained flow network, we predict the flows from
an intermediate frame to the two input images. To do this, we propose to encode
the bidirectional flows into a coordinate-based network, powered by a
hypernetwork, to obtain a continuous representation of the flow across time.
Once we obtain the estimated flows, we use them within an existing blending
network to obtain the final intermediate frame. Through extensive experiments,
we demonstrate that our approach is able to produce significantly better
results than state-of-the-art frame interpolation algorithms.
