1 code implementation • 12 Oct 2023 • Paul Roetzer, Ahmed Abbas, Dongliang Cao, Florian Bernard, Paul Swoboda
In this work we propose to combine the advantages of learningbased and combinatorial formalisms for 3D shape matching.
1 code implementation • 28 Jan 2023 • Ahmed Abbas, Paul Swoboda
We propose a graph clustering formulation based on multicut (a. k. a.
1 code implementation • 23 May 2022 • Ahmed Abbas, Paul Swoboda
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.
2 code implementations • 4 Feb 2022 • Paul Swoboda, Bjoern Andres, Andrea Hornakova, Florian Bernard, Jannik Irmai, Paul Roetzer, Bogdan Savchynskyy, David Stein, Ahmed Abbas
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.
1 code implementation • CVPR 2022 • Ahmed Abbas, Paul Swoboda
We present a massively parallel Lagrange decomposition method for solving 0--1 integer linear programs occurring in structured prediction.
1 code implementation • CVPR 2022 • Ahmed Abbas, Paul Swoboda
We propose a highly parallel primal-dual algorithm for the multicut (a. k. a.
2 code implementations • NeurIPS 2021 • Ahmed Abbas, Paul Swoboda
We propose a fully differentiable architecture for simultaneous semantic and instance segmentation (a. k. a.
Ranked #8 on Panoptic Segmentation on Cityscapes test
1 code implementation • ICCV 2019 • Ahmed Abbas, Paul Swoboda
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.