A Lightweight Optical Flow CNN -Revisiting Data Fidelity and Regularization.

Over four decades, the majority addresses the problem of optical flow estimation using variational methods. With the advance of machine learning, some recent works have attempted to address the problem using convolutional neural network (CNN) and have showed promising results. FlowNet2 [1] , the state-of-the-art CNN, requires over 160M parameters to achieve accurate flow estimation.