Document parsing is essential for converting unstructured and semi-structured documents-
such as contracts, academic papers, and invoices-into structured, machine-readable data …

Tables contain factual and quantitative data accompanied by various structures and
contents that pose challenges for machine comprehension. Previous methods generally …

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 …

Recently visually-situated text parsing (VsTP) has experienced notable advancements
driven by the increasing demand for automated document understanding and the …

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 …

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 …

Table structure recognition (TSR) is crucial for document analysis, particularly for medical
examination report tables (MERTs), impacting efficiency and decision-making in healthcare …

As one of the most commonly used and important data carriers, tables have the advantages
of high structuring, strong readability and strong flexibility. However, in reality, tables usually …

In today's information age, table images play a crucial role in storing structured information,
making table image recognition technology an essential component in many fields …

In the digital era, table structure recognition technology is a critical tool for processing and
analyzing large volumes of tabular data. Previous methods primarily focus on visual aspects …