A Survey on One-Shot Multi-Object Tracking Algorithm

Visual multiple object tracking (MOT) has become a hot issue in computer vision and intelligent analysis of video images. In recent years, with the development of deep learning and practical application needs, more and more one-shot MOT algorithms with outstanding performance have been proposed, attracting much attention from researchers. This paper systematically reviews the popular one-shot MOT algorithms. From different construction ideas, the paper summarizes the motivation, framework design, strengths and weaknesses of methods, research trends, etc. Afterwards, we compare the performances of the one-shot MOT algorithms on the public testing set MOT Challenge, and quantitatively analyze the advantages and limitations of different one-shot methods. Finally, some future thoughts, foresight, and key issues that need to be focused on are introduced based on the research status.