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Abstract: This talk will introduce our paper recently accepted as Oral to ECCV2024. Gate quantum computers generate significant interest due to their potential to solve certain difficult problems such as prime factorization in polynomial time. Computer vision researchers have long been attracted to the power of quantum computers. Robust fitting, which is fundamentally important to many computer vision pipelines, has recently been shown to be amenable to gate quantum computing. The previous proposed solution was to compute Boolean influence as a measure of outlyingness using the Bernstein-Vazirani quantum circuit. However, the method assumed a quantum implementation of an L-infinity feasibility test, which has not been demonstrated. In our paper, we take a big stride towards quantum robust fitting: we propose a quantum circuit to solve the L-infinity feasibility test in the 1D case, which allows us to demonstrate for the first time quantum robust fitting on a real gate quantum computer, the IonQ Aria. We also show how 1D Boolean influences can be accumulated to compute Boolean influences for higher-dimensional non-linear models, which we experimentally validate on real benchmark datasets. This talk is intended for a computer vision audience with minimal quantum physics background.