The accurate estimation of motion in image sequences is
of central importance to numerous computer vision applications.
Most competitive algorithms compute flow fields
by minimi...
Andreas Wedel, Daniel Cremers, Thomas Pock, Horst ...
Abstract. Virtually all variational methods for motion estimation regularize the gradient of the flow field, which introduces a bias towards piecewise constant motions in weakly te...
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...
—Optical flow estimation is classically marked by the requirement of dense sampling in time. While coarse-to-fine warping schemes have somehow relaxed this constraint, there is...
Although the recent advances in the sparse representations of images have achieved outstanding denosing results, removing real, structured noise in digital videos remains a challen...
Abstract. In this paper, we propose a variational framework for computing a superresolved image of a scene from an arbitrary input video. To this end, we employ a recently proposed...
Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Da...