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AbstractPerson reidentification rate has become a challenging research topic in the field of computer vision due to the fact that person appearance is easily affected by lighting, posture and perspective. In order to make full use of the continuity of video data on the time line and the unstructured relationship of features, a video person reidentification algorithm combining the neural ordinary differential equation with the graph convolution network is proposed in this paper. First, adoi:10.1186/s13634-021-00747-1 fatcat:vxl3awf5yjgbni6nzbbum3wm6i