26 citations · 37 across the 4 of their papers we have counts for
5 papers
On the Geometric Mechanics of Assignment Flows for Metric Data Labeling
Fabrizio Savarino, Peter Albers, Christoph Schnörr
Metric data labeling refers to the task of assigning one of multiple predefined labels to every given datapoint based on the metric distance between label and data. This assignment…
Continuous-Domain Assignment Flows
Fabrizio Savarino, Christoph Schnörr
Assignment flows denote a class of dynamical models for contextual data labeling (classification) on graphs. We derive a novel parametrization of assignment flows that reveals how…
Learning Adaptive Regularization for Image Labeling Using Geometric Assignment
Ruben Hühnerbein, Fabrizio Savarino, Stefania Petra +1
We study the inverse problem of model parameter learning for pixelwise image labeling, using the linear assignment flow and training data with ground truth. This is accomplished by…
Geometric Numerical Integration of the Assignment Flow
Alexander Zeilmann, Fabrizio Savarino, Stefania Petra +1
The assignment flow is a smooth dynamical system that evolves on an elementary statistical manifold and performs contextual data labeling on a graph. We derive and introduce the li…
Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment
Ruben Hühnerbein, Fabrizio Savarino, Freddie Åström +1
We introduce a novel approach to Maximum A Posteriori inference based on discrete graphical models. By utilizing local Wasserstein distances for coupling assignment measures across…