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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 machine learning (AI/ML). Computer vision, the fastest growing field in the AI/ML field, has also seen potential applications of quantum computing to solve computer vision tasks. In this paper, we discuss the current approach of utilizing quantum computing to computer vision. In particular, we firstly elaborate on classical approaches to solving several computer vision tasks, then briefly describe the background of different paradigms of quantum computers, i.e., the adiabatic quantum computer (quantum annealer), and the gate model, also known as the universal quantum computer. Subsequently, we summarize the problem formulation and quantum computing-based solutions to computer vision tasks that appeared in the major AI/ML conferences in the past years. Additionally, the strengths and drawbacks of each case are also discussed, providing beneficial insights into the current state of quantum computing usage for computer vision.
Larasati et al. (Mon,) studied this question.