Semantic page segmentation of vector graphics documents

Abstract

Disclosed systems and methods categorize text regions of an electronic document into document object types based on a combination of semantic information and appearance information from the electronic document. A page segmentation application executing on a computing device accesses textual feature representations that represent text portions in a vector space, where a set of pixels from the page is mapped to a textual feature representation. The page segmentation application generates a visual feature representation, which corresponds to an appearance of a document portion including the set of pixels, by applying a neural network to the page of the electronic document. The page segmentation application generates an output page segmentation of the electronic document by applying the neural network to the textual feature representation and the visual feature representation.