Quantum Motion Segmentation
This addresses motion segmentation for computer vision, but it is incremental as it adapts quantum methods to an existing problem without broad breakthroughs.
The paper tackles motion segmentation by introducing the first algorithm using adiabatic quantum optimization, achieving performance on par with state-of-the-art methods on instances compatible with modern quantum annealers.
Motion segmentation is a challenging problem that seeks to identify independent motions in two or several input images. This paper introduces the first algorithm for motion segmentation that relies on adiabatic quantum optimization of the objective function. The proposed method achieves on-par performance with the state of the art on problem instances which can be mapped to modern quantum annealers.