We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)
image analysis to end users without substantial computational expertise. It contains pre …

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 …

Segmentation algorithms are prone to make topological errors on fine-scale struc-tures, eg,
broken connections. We propose a novel method that learns to segment with correct …

Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or
roads, is relevant to many fields of research. For such structures, the topology is their most …

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 …

For the segmentation of moving objects in videos, the analysis of long-term point trajectories
has been very popular recently. In this paper, we formulate the segmentation of a video …

In the segmentation of fine-scale structures from natural and biomedical images, per-pixel
accuracy is not the only metric of concern. Topological correctness, such as vessel …

Szeliski et al. published an influential study in 2006 on energy minimization methods for
Markov random fields. This study provided valuable insights in choosing the best …

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 …

Significant progress has been made in the field of computer vision because of the
development of supervised machine learning algorithms, which efficiently extract information …