In this paper, we introduce a mathematical framework for obtaining spatially smooth
semantic labelings of 3D point clouds from a pointwise classification. We argue that …

We propose a fast splitting approach to the classical variational formulation of the image
partitioning problem, which is frequently referred to as the Potts or piecewise constant …

We present and compare various types of discretizations which have been proposed to
approximate the total variation (mostly, of a gray-level image in two dimensions). We discuss …

Techniques that jointly perform dense 3D reconstruction and semantic segmentation have
recently shown very promising results. One major restriction so far is that they can often only …

We present a convergence rate analysis of the Rudin–Osher–Fatemi (ROF) denoising
problem for two different discretizations of the total variation. The first is the standard …

Variable splitting schemes for the function space version of the image reconstruction
problem with total variation regularization (TV-problem) in its primal and pre-dual …

All imaging modalities such as computed tomography, emission tomography and magnetic
resonance imaging require a reconstruction approach to produce an image. A common …

Lifting methods allow to transform hard variational problems such as segmentation and
optical flow estimation into convex problems in a suitable higher-dimensional space. The …

We present a novel variational approach to image restoration (eg, denoising, inpainting,
labeling) that enables us to complement established variational approaches with a …

Many problems in imaging and low-level vision can be formulated as nonconvex variational
problems. A promising class of approaches to tackle such problems are convex relaxation …