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Dagmar Kainmüller

3 accepted papers

2022

A Comparative Study of Graph Matching Algorithms in Computer Vision

ECCV 2022poster

"The graph matching optimization problem is an essential component for many tasks in computer vision, such as bringing two deformable objects in correspondence. Naturally, a wide range of applicable algorithms have been proposed in the last decades. Since a common standard benchmark has not been dev…

2021

Fusion Moves for Graph Matching

ICCV 2021poster

We contribute to approximate algorithms for the quadratic assignment problem also known as graph matching. Inspired by the success of the fusion moves technique developed for multilabel discrete Markov random fields, we investigate its applicability to graph matching. In particular, we show how fusi…

Cited by 16PDFcodeScholar
2021

How Shift Equivariance Impacts Metric Learning for Instance Segmentation

ICCV 2021poster

Metric learning has received conflicting assessments concerning its suitability for solving instance segmentation tasks. It has been dismissed as theoretically flawed due to the shift equivariance of the employed CNNs and their respective inability to distinguish same-looking objects. Yet it has bee…

Cited by 5PDFcodeScholar