Search Results for author:
Found 35 papers, 6 papers with code
OpenGM: A C++ Library for Discrete Graphical Models
OpenGM is a C++ template library for defining discrete graphical models and performing inference on these models, using a wide range of state-of-the-art algorithms.
Reconstructing Loopy Curvilinear Structures Using Integer Programming
We propose a novel approach to automated delineation of linear structures that form complex and potentially loopy networks.
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems
However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.
Estimating Maximally Probable Constrained Relations by Mathematical Programming
Estimating (learning) a maximally probable measure, given (a training set of) related and unrelated pairs, is a convex optimization problem.
Efficient Decomposition of Image and Mesh Graphs by Lifted Multicuts
a pixel grid graph have received little attention, firstly, because the MP is NP-hard and instances w. r. t.
Subgraph Decomposition for Multi-Target Tracking
Tracking multiple targets in a video, based on a finite set of detection hypotheses, is a persistent problem in computer vision.
Convexity Shape Constraints for Image Segmentation
Incorporating such prior knowledge into models and algorithms for image segmentation is highly desirable, yet can be non-trivial.
Moral Lineage Tracing
We propose an integer linear program (ILP) whose feasible solutions define a decomposition of each image in a sequence into cells (segmentation), and a lineage forest of cells across images (tracing).
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
This paper considers the task of articulated human pose estimation of multiple people in real world images.
Ranked #2 on
Multi-Person Pose Estimation
on WAF
Motion Trajectory Segmentation via Minimum Cost Multicuts
For the segmentation of moving objects in videos, the analysis of long-term point trajectories has been very popular recently.
Convexification of Learning from Constraints
For common loss and regularization functions, this optimization problem assumes the form of a mixed integer program (MIP) whose objective function is non-convex.
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
The goal of this paper is to advance the state-of-the-art of articulated pose estimation in scenes with multiple people.
Ranked #1 on
Multi-Person Pose Estimation
on WAF
The Minimum Cost Connected Subgraph Problem in Medical Image Analysis
Several important tasks in medical image analysis can be stated in the form of an optimization problem whose feasible solutions are connected subgraphs.
A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects
Recently, Minimum Cost Multicut Formulations have been proposed and proven to be successful in both motion trajectory segmentation and multi-target tracking scenarios.
Multi-Person Tracking by Multicut and Deep Matching
In [1], we proposed a graph-based formulation that links and clusters person hypotheses over time by solving a minimum cost subgraph multicut problem.
Joint Graph Decomposition and Node Labeling: Problem, Algorithms, Applications
In order to find feasible solutions efficiently, we define two local search algorithms that converge monotonously to a local optimum, offering a feasible solution at any time.
InstanceCut: from Edges to Instances with MultiCut
This work addresses the task of instance-aware semantic segmentation.
ArtTrack: Articulated Multi-person Tracking in the Wild
In this paper we propose an approach for articulated tracking of multiple people in unconstrained videos.
Ranked #7 on
Keypoint Detection
on MPII Multi-Person
A Message Passing Algorithm for the Minimum Cost Multicut Problem
We propose a dual decomposition and linear program relaxation of the NP -hard minimum cost multicut problem.
Efficient Algorithms for Moral Lineage Tracing
Lineage tracing, the joint segmentation and tracking of living cells as they move and divide in a sequence of light microscopy images, is a challenging task.
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs
This paper introduces a novel algorithm for transductive inference in higher-order MRFs, where the unary energies are parameterized by a variable classifier.
Multiple People Tracking by Lifted Multicut and Person Re-Identification
This allows us to reward tracks that assign detections of similar appearance to the same person in a way that does not introduce implausible solutions.
Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications
In order to find feasible solutions efficiently, we define two local search algorithms that converge monotonously to a local optimum, offering a feasible solution at any time.
Analysis and Optimization of Graph Decompositions by Lifted Multicuts
We study the set of all decompositions (clusterings) of a graph through its characterization as a set of lifted multicuts.
Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering
Weighted correlation clustering is hard to solve and hard to approximate for general graphs.
End-to-end Learning for Graph Decomposition
The new optimization problem can be viewed as a Conditional Random Field (CRF) in which the random variables are associated with the binary edge labels of the initial graph and the hard constraints are introduced in the CRF as high-order potentials.
Inapproximability of a Pair of Forms Defining a Partial Boolean Function
We consider the problem of jointly minimizing forms of two Boolean functions $f, g \colon \{0, 1\}^J \to \{0, 1\}$ such that $f + g \leq 1$ and so as to separate disjoint sets $A \cup B \subseteq \{0, 1\}^J$ such that $f(A) = \{1\}$ and $g(B) = \{1\}$.
Structured Prediction Problem Archive
In order to facilitate algorithm development for their numerical solution, we collect in one place a large number of datasets in easy to read formats for a diverse set of problem classes.
A Polyhedral Study of Lifted Multicuts
Recently, a lifting of multicuts from a graph $G = (V, E)$ to an augmented graph $\hat G = (V, E \cup F)$ has been proposed in the field of image analysis, with the goal of obtaining a more expressive characterization of graph decompositions in which it is made explicit also for pairs $F \subseteq \tbinom{V}{2} \setminus E$ of non-neighboring nodes whether these are in the same or distinct components.
Partial Optimality in Cubic Correlation Clustering
The higher-order correlation clustering problem is an expressive model, and recently, local search heuristics have been proposed for several applications.
Correlation Clustering of Bird Sounds
We address the following questions: How accurate is this clustering, compared to a classification of the test set?
A Graph Multi-separator Problem for Image Segmentation
We propose a novel abstraction of the image segmentation task in the form of a combinatorial optimization problem that we call the multi-separator problem.
A 4-approximation algorithm for min max correlation clustering
We introduce a lower bounding technique for the min max correlation clustering problem and, based on this technique, a combinatorial 4-approximation algorithm for complete graphs.
Box Facets and Cut Facets of Lifted Multicut Polytopes
For $F = \emptyset$, the problem specializes to the multicut problem, and for $E = \tbinom{V}{2}$ to the clique partitioning problem.
Correlation Clustering of Organoid Images
In biological and medical research, scientists now routinely acquire microscopy images of hundreds of morphologically heterogeneous organoids and are then faced with the task of finding patterns in the image collection, i. e., subsets of organoids that appear similar and potentially represent the same morphological class.
