Search Results for author:
Found 8 papers, 6 papers with code
Fast Discrete Optimisation for Geometrically Consistent 3D Shape Matching
In this work we propose to combine the advantages of learning-based and combinatorial formalisms for 3D shape matching.
ClusterFuG: Clustering Fully connected Graphs by Multicut
We propose a graph clustering formulation based on multicut (a. k. a.
DOGE-Train: Discrete Optimization on GPU with End-to-end Training
Our solver achieves significantly faster performance and better dual objectives than its non-learned version, achieving close to optimal objective values of LP relaxations of very large structured prediction problems and on selected combinatorial ones.
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.
FastDOG: Fast Discrete Optimization on GPU
We present a massively parallel Lagrange decomposition method for solving 0--1 integer linear programs occurring in structured prediction.
RAMA: A Rapid Multicut Algorithm on GPU
We propose a highly parallel primal-dual algorithm for the multicut (a. k. a.
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach
We propose a fully differentiable architecture for simultaneous semantic and instance segmentation (a. k. a.
Ranked #8 on
Panoptic Segmentation
on Cityscapes test
Bottleneck potentials in Markov Random Fields
We consider general discrete Markov Random Fields(MRFs) with additional bottleneck potentials which penalize the maximum (instead of the sum) over local potential value taken by the MRF-assignment.
