  We propose WOFT -- a novel method for planar object tracking that estimates a
full 8 degrees-of-freedom pose, i.e. the homography w.r.t. a reference view.
The method uses a novel module that leverages dense optical flow and assigns a
weight to each optical flow correspondence, estimating a homography by weighted
least squares in a fully differentiable manner. The trained module assigns zero
weights to incorrect correspondences (outliers) in most cases, making the
method robust and eliminating the need of the typically used non-differentiable
robust estimators like RANSAC. The proposed weighted optical flow tracker
(WOFT) achieves state-of-the-art performance on two benchmarks, POT-210 and
POIC, tracking consistently well across a wide range of scenarios.
