In recent years, visual relocalization has emerged as a pivotal task in the domains of 3D computer vision and learning based methodologies, witnessing substantial advances due to the evolution of learning based methodologies. This article reviews the current landscape and recent developments in visual relocalization research. It methodically discusses visual relocalization tasks, delineates fundamental solution methodologies, categorizes existing studies, and outlines research objectives within this field. By systematically organizing and elucidating the stateof-the-art of visual relocalization through the lens of learning based methodologies, this paper aims to provide a comprehensive analysis to aid researchers to swiftly grasp the essence of the research problem. It offers a lucid overview of the specific advances in various research directions, thereby facilitating effective applications and further investigation. Additionally, this article anticipates future research trajectories to address visual relocalization challenges.