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...
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
We describe how to build a VIDEOPLACE-like vision-driven user interface using "optical-flow" measurements. The optical-flow denotes the estimated movement of an image pat...
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
We propose an algorithm for large displacement opti-
cal flow estimation which does not require the commonly
used coarse-to-fine warping strategy. It is based on a
quadratic rel...