Multiple object tracking gained a lot of interest from researchers in recent years, and it has
become one of the trending problems in computer vision, especially with the recent …

New high-performance computing architectures are becoming operative, in addition to
exascale computers. Quantum computers (QC) solve optimization problems with …

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 …

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 …

Real-time multi-object tracking (MOT) is a complex task involving detecting and tracking
multiple objects. After the objects are detected, they are assigned markers, and their …

We present a hybrid classical-quantum framework based on the Frank-Wolfe algorithm, Q-
FW, for solving quadratic, linearly-constrained, binary optimization problems on quantum …

This paper proposes a quantum computing-based algorithm to solve the single image super-
resolution (SISR) problem. One of the well-known classical approaches for SISR relies on …

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 …

Computer Vision (CV) labeling problems play a pivotal role in low-level vision. For decades,
it has been known that these problems can be elegantly formulated as discrete energy …

We propose a circuit-level backdoor attack, QTrojan, against Quantum Neural Networks
(QNNs) in this paper. QTrojan is implemented by a few quantum gates inserted into the …