Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

From the autonomous car driving to medical diagnosis, the requirement of the task of image
segmentation is everywhere. Segmentation of an image is one of the indispensable tasks in …

This paper considers the task of articulated human pose estimation of multiple people in real
world images. We propose an approach that jointly solves the tasks of detection and pose …

Models for computer vision are commonly defined either wrt low-level concepts such as
pixels that are to be grouped, or wrt high-level concepts such as semantic objects that are to …

The correlation clustering problem identifies clusters in a set of objects when the qualitative
information about objects' mutual similarities or dissimilarities is given in a signed network …

In this work, we describe a method for large-scale 3D cell-tracking through a segmentation
selection approach. The proposed method is effective at tracking cells across large …

Abstract Formulations of the Image Decomposition Problem as a Multicut Problem (MP) wrt a
superpixel graph have received considerable attention. In contrast, instances of the MP wrt a …

Image partitioning, or segmentation without semantics, is the task of decomposing an image
into distinct segments; or equivalently, the task of detecting closed contours in an image …

The minimum cost lifted multicut problem is a generalization of the multicut problem (also
known as correlation clustering) and is a means to optimizing a decomposition of a graph …

Recently, unsupervised image segmentation has become increasingly popular. Starting
from a superpixel segmentation, an edge-weighted region adjacency graph is constructed …