Tables and figures are usually used to present information in a structured and visual way in
scientific documents. Understanding the tables and figures in scientific documents is …

Tables organize valuable content in a concise and compact representation. This content is
extremely valuable for systems such as search engines, Knowledge Graph's, etc, since they …

We present a new table structure recognition (TSR) approach, called TSRFormer, to robustly
recognizing the structures of complex tables with geometrical distortions from various table …

This paper provides a comprehensive overview of the process for information retrieval from
invoices. Invoices serve as proof of purchase and contain important information, including …

Table structure recognition (TSR) aims at extracting tables in images into machine-
understandable formats. Recent methods solve this problem by predicting the adjacency …

Abstract Recent advanced Table Structure Recognition (TSR) models adopt image-to-text
solutions to parse table structure. These methods can be formulated as image caption …

Abstract Geometric Deep Learning has recently attracted significant interest in a wide range
of machine learning fields, including document analysis. The application of Graph Neural …

We present a new table structure recognition (TSR) approach, called TSRFormer, to robustly
recognize the structures of complex tables with geometrical distortions from various table …

Tables are widely used in research and business, which are suitable for human
consumption, but not easily machine-processable, particularly when tables are present in …

All tables can be represented as grids. Based on this observation, we propose GridFormer, a
novel approach for interpreting unconstrained table structures by predicting the vertex and …