We benchmark the quantum processing units of the largest quantum annealers to date, the
5000+ qubit quantum annealer Advantage and its 2000+ qubit predecessor D-Wave 2000Q …

As the development in quantum computation is on the rise, its potential application in
various research areas has been investigated, including to artificial intelligence and …

Abstract Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection
paradigm, where object detections are associated through time. The association step …

We present SyNoRiM, a novel way to jointly register multiple non-rigid shapes by
synchronizing the maps that relate learned functions defined on the point clouds. Even …

Fitting geometric models onto outlier contaminated data is provably intractable. Many
computer vision systems rely on random sampling heuristics to solve robust fitting, which do …

Jointly matching multiple, non-rigidly deformed 3D shapes is a challenging, NP-hard
problem. A perfect matching is necessarily cycle-consistent: Following the pairwise point …

Optimisation algorithms designed to work on quantum computers or other specialised
hardware have been of research interest in recent years. Commercial solvers that use …

We propose an iterative method for estimating rigid transformations from point sets using
adiabatic quantum computation. Compared to existing quantum approaches, our method …

We study large-scale applications using a GPU-accelerated version of the massively parallel
Jülich universal quantum computer simulator (JUQCS–G). First, we benchmark JUWELS …

Geometric model fitting is a challenging but fundamental computer vision problem. Recently,
quantum optimization has been shown to enhance robust fitting for the case of a single …