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Human activities are hugely restricted by COVID-19, recently. Robots that canconduct inter-floor navigation attract much public attention, since they cansubstitute human workers to conduct the service work. However, current robotseither depend on human assistance or elevator retrofitting, and fullyautonomous inter-floor navigation is still not available. As the very firststep of inter-floor navigation, elevator button segmentation and recognitionhold an important position. Therefore, we release the first large-scalepublicly available elevator panel dataset in this work, containing 3,718 panelimages with 35,100 button labels, to facilitate more powerful algorithms onautonomous elevator operation. Together with the dataset, a number of deeplearning based implementations for button segmentation and recognition are alsoreleased to benchmark future methods in the community. The dataset will beavailable at \url{https://github.com/zhudelong/elevator_button_recognition

A Large-Scale Dataset for Benchmarking Elevator Button Segmentation and Character Recognition