In this paper, we propose novel algorithms for total variation (TV) based image restoration and parameter estimation utilizing variational distribution approximations. Within the h...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
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...
This paper addresses the problem of mapping images between different vision sensors. Such a mapping could be modeled as a sampling problem that has to encompass the change of geom...
Estimating the disparity field between two stereo images is a common task in computer vision, e.g., to determine a dense depth map. Variational methods currently are among the mos...
We present a variational approach to jointly estimate a displacement map and a superresolution texture for a 3D model from multiple calibrated views. The superresolution image form...