Tables are everywhere, from scientific journals, papers, websites, and newspapers all the
way to items we buy at the supermarket. Detecting them is thus of utmost importance to …

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 …

This paper presents a comprehensive evaluation of the Optical Character Recognition
(OCR) capabilities of the recently released GPT-4V (ision), a Large Multimodal Model …

Table structure recognition aims to extract the logical and physical structure of unstructured
table images into a machine-readable format. The latest end-to-end image-to-text …

In this paper, we present StrucTexTv2, an effective document image pre-training framework,
by performing masked visual-textual prediction. It consists of two self-supervised pre-training …

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 …

Recently, table structure recognition has achieved impressive progress with the help of deep
graph models. Most of them exploit single visual cues of tabular elements or simply combine …

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 …

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 …