4 citations · 6 across the 7 of their papers we have counts for
7 papers
LiteTracker: Leveraging Temporal Causality for Accurate Low-latency Tissue Tracking
Mert Asim Karaoglu, Wenbo Ji, Ahmed Abbas +3
Tissue tracking plays a critical role in various surgical navigation and extended reality (XR) applications. While current methods trained on large synthetic datasets achieve high…
DiscoMatch: Fast Discrete Optimisation for Geometrically Consistent 3D Shape Matching
Paul Roetzer, Ahmed Abbas, Dongliang Cao +2
In this work we propose to combine the advantages of learningbased and combinatorial formalisms for 3D shape matching. While learningbased methods lead to state-of-the-art matching…
ClusterFuG: Clustering Fully connected Graphs by Multicut
Ahmed Abbas, Paul Swoboda
We propose a graph clustering formulation based on multicut (a.k.a. weighted correlation clustering) on the complete graph. Our formulation does not need specification of the graph…
DOGE-Train: Discrete Optimization on GPU with End-to-end Training
Ahmed Abbas, Paul Swoboda
We present a fast, scalable, data-driven approach for solving relaxations of 0-1 integer linear programs. We use a combination of graph neural networks (GNN) and the Lagrange decom…
Structured Prediction Problem Archive
Paul Swoboda, Bjoern Andres, Andrea Hornakova +6
Structured prediction problems are one of the fundamental tools in machine learning. In order to facilitate algorithm development for their numerical solution, we collect in one pl…
FastDOG: Fast Discrete Optimization on GPU
Ahmed Abbas, Paul Swoboda
We present a massively parallel Lagrange decomposition method for solving 0--1 integer linear programs occurring in structured prediction. We propose a new iterative update scheme…
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach
Ahmed Abbas, Paul Swoboda
We propose a fully differentiable architecture for simultaneous semantic and instance segmentation (a.k.a. panoptic segmentation) consisting of a convolutional neural network and a…