Dense motion estimations obtained from optical flow techniques play a significant role in
many image processing and computer vision tasks. Remarkable progress has been made in
both theory and its application in practice. In this paper, we provide a systematic review of
recent optical flow techniques with a focus on the variational method and approaches based
on Convolutional Neural Networks (CNNs). These two categories have led to state-of-the-art
performance. We discuss recent modifications and extensions of the original model, and …