113 citations · 348 across the 23 of their papers we have counts for
8 papers · 1 filter
ArtTrack: Articulated Multi-person Tracking in the Wild
Eldar Insafutdinov, Mykhaylo Andriluka, Leonid Pishchulin +4
In this paper we propose an approach for articulated tracking of multiple people in unconstrained videos. Our starting point is a model that resembles existing architectures for si…
InstanceCut: from Edges to Instances with MultiCut
Alexander Kirillov, Evgeny Levinkov, Bjoern Andres +2
This work addresses the task of instance-aware semantic segmentation. Our key motivation is to design a simple method with a new modelling-paradigm, which therefore has a different…
Joint Graph Decomposition and Node Labeling: Problem, Algorithms, Applications
Evgeny Levinkov, Jonas Uhrig, Siyu Tang +7
We state a combinatorial optimization problem whose feasible solutions define both a decomposition and a node labeling of a given graph. This problem offers a common mathematical a…
Multi-Person Tracking by Multicut and Deep Matching
Siyu Tang, Bjoern Andres, Mykhaylo Andriluka +1
In [1], we proposed a graph-based formulation that links and clusters person hypotheses over time by solving a minimum cost subgraph multicut problem. In this paper, we modify and…
A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects
Margret Keuper, Siyu Tang, Yu Zhongjie +3
Recently, Minimum Cost Multicut Formulations have been proposed and proven to be successful in both motion trajectory segmentation and multi-target tracking scenarios. Both tasks b…
The Minimum Cost Connected Subgraph Problem in Medical Image Analysis
Markus Rempfler, Bjoern Andres, Bjoern H. Menze
Several important tasks in medical image analysis can be stated in the form of an optimization problem whose feasible solutions are connected subgraphs. Examples include the recons…
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
Eldar Insafutdinov, Leonid Pishchulin, Bjoern Andres +2
The goal of this paper is to advance the state-of-the-art of articulated pose estimation in scenes with multiple people. To that end we contribute on three fronts. We propose (1) i…
Convexification of Learning from Constraints
Iaroslav Shcherbatyi, Bjoern Andres
Regularized empirical risk minimization with constrained labels (in contrast to fixed labels) is a remarkably general abstraction of learning. For common loss and regularization fu…