research
∙
08/03/2023
A Multidimensional Analysis of Social Biases in Vision Transformers
The embedding spaces of image models have been shown to encode a range o...
share
research
∙
06/20/2023
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
Obtaining large pre-trained models that can be fine-tuned to new tasks w...
research
∙
01/28/2023
ClusterFuG: Clustering Fully connected Graphs by Multicut
We propose a graph clustering formulation based on multicut (a.k.a. weig...
research
∙
12/04/2022
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering
Collecting large-scale medical datasets with fully annotated samples for...
research
∙
07/01/2022
A Comparative Study of Graph Matching Algorithms in Computer Vision
The graph matching optimization problem is an essential component for ma...
research
∙
05/23/2022
DOGE-Train: Discrete Optimization on GPU with End-to-end Training
We present a fast, scalable, data-driven approach for solving linear rel...
research
∙
04/27/2022
A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching
We present a scalable combinatorial algorithm for globally optimizing ov...
research
∙
02/04/2022
Structured Prediction Problem Archive
Structured prediction problems are one of the fundamental tools in machi...
research
∙
11/23/2021
LMGP: Lifted Multicut Meets Geometry Projections for Multi-Camera Multi-Object Tracking
Multi-Camera Multi-Object Tracking is currently drawing attention in the...
research
∙
11/19/2021
FastDOG: Fast Discrete Optimization on GPU
We present a massively parallel Lagrange decomposition method for solvin...
research
∙
09/04/2021
RAMA: A Rapid Multicut Algorithm on GPU
We propose a highly parallel primal-dual algorithm for the multicut (a.k...
research
∙
08/24/2021
Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths
We present an efficient approximate message passing solver for the lifte...
research
∙
06/06/2021
Combinatorial Optimization for Panoptic Segmentation: An End-to-End Trainable Approach
We propose an end-to-end trainable architecture for simultaneous semanti...
research
∙
06/25/2020
Lifted Disjoint Paths with Application in Multiple Object Tracking
We present an extension to the disjoint paths problem in which additiona...
research
∙
04/14/2020
A Primal-Dual Solver for Large-Scale Tracking-by-Assignment
We propose a fast approximate solver for the combinatorial problem known...
research
∙
04/14/2020
Exact MAP-Inference by Confining Combinatorial Search with LP Relaxation
We consider the MAP-inference problem for graphical models, which is a v...
research
∙
03/25/2020
Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers
Building on recent progress at the intersection of combinatorial optimiz...
research
∙
04/17/2019
Bottleneck potentials in Markov Random Fields
We consider general discrete Markov Random Fields(MRFs) with additional ...
research
∙
11/26/2018
Higher-order Projected Power Iterations for Scalable Multi-Matching
The matching of multiple objects (e.g. shapes or images) is a fundamenta...
research
∙
06/13/2018
MAP inference via Block-Coordinate Frank-Wolfe Algorithm
We present a new proximal bundle method for Maximum-A-Posteriori (MAP) i...
research
∙
12/16/2016
A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching
We study the quadratic assignment problem, in computer vision also known...
research
∙
12/16/2016
A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems
We propose a general dual ascent framework for Lagrangean decomposition ...
research
∙
12/16/2016
A Message Passing Algorithm for the Minimum Cost Multicut Problem
We propose a dual decomposition and linear program relaxation of the NP ...
research
∙
01/09/2016
Multicuts and Perturb & MAP for Probabilistic Graph Clustering
We present a probabilistic graphical model formulation for the graph clu...
research
∙
08/31/2015
Maximum Persistency via Iterative Relaxed Inference with Graphical Models
We consider the NP-hard problem of MAP-inference for undirected discrete...
research
∙
10/24/2014
Partial Optimality by Pruning for MAP-Inference with General Graphical Models
We consider the energy minimization problem for undirected graphical mod...
research
∙
01/16/2013
