Video Instance Segmentation is All You Need for Linking Geographic Entities from Historical Maps

Numerous historical research endeavors necessitate synthesizing information derived from multiple historical maps. Linking geographic entities across diverse maps has posed a persistent challenge for researchers. The conventional approach involves a two-step pipeline, initially detecting entities within individual maps and subsequently associating entities from different maps through a linking post-processing step. This paper introduces an innovative solution by conceptualizing historical maps as a 3D spatiotemporal volume. It advocates for simultaneous segmentation and association by employing video instance segmentation. The experimental findings demonstrate the superiority of the proposed method over the traditional approach, achieving a notable 0.2 F1-score improvement. Furthermore, its end-toend nature significantly streamlines the workflow for geographic entity alignment, thereby substantially enhancing the level of automation.