56 citations · 199 across the 40 of their papers we have counts for
9 papers · 1 filter
Assignment Flow for Order-Constrained OCT Segmentation
D. Sitenko, B. Boll, C. Schnörr
At the present time Optical Coherence Tomography (OCT) is among the most commonly used non-invasive imaging methods for the acquisition of large volumetric scans of human retinal t…
Image Labeling by Assignment
Freddie Åström, Stefania Petra, Bernhard Schmitzer +1
We introduce a novel geometric approach to the image labeling problem. Abstracting from specific labeling applications, a general objective function is defined on a manifold of sto…
Multicuts and Perturb & MAP for Probabilistic Graph Clustering
Jörg Hendrik Kappes, Paul Swoboda, Bogdan Savchynskyy +2
We present a probabilistic graphical model formulation for the graph clustering problem. This enables to locally represent uncertainty of image partitions by approximate marginal d…
Globally Optimal Joint Image Segmentation and Shape Matching Based on Wasserstein Modes
Bernhard Schmitzer, Christoph Schnörr
A functional for joint variational object segmentation and shape matching is developed. The formulation is based on optimal transport w.r.t. geometric distance and local feature si…
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems
Jörg H. Kappes, Bjoern Andres, Fred A. Hamprecht +10
Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov Random Fields (MRF). This study provided valuable insights in choosing the best opt…
Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization
Fabian Rathke, Stefan Schmidt, Christoph Schnörr
With the introduction of spectral-domain optical coherence tomography (OCT), resulting in a significant increase in acquisition speed, the fast and accurate segmentation of 3-D OCT…
Higher-order Segmentation via Multicuts
Joerg Hendrik Kappes, Markus Speth, Gerhard Reinelt +1
Multicuts enable to conveniently represent discrete graphical models for unsupervised and supervised image segmentation, in the case of local energy functions that exhibit symmetri…
Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem
Jan Lellmann, Frank Lenzen, Christoph Schnörr
We consider a variational convex relaxation of a class of optimal partitioning and multiclass labeling problems, which has recently proven quite successful and can be seen as a con…
Continuous Multiclass Labeling Approaches and Algorithms
Jan Lellmann, Christoph Schnörr
We study convex relaxations of the image labeling problem on a continuous domain with regularizers based on metric interaction potentials. The generic framework ensures existence o…