The first phase of table recognition is to detect the tabular area in a document.
Subsequently, the tabular structures are recognized in the second phase in order to extract …

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

Important information that relates to a specific topic in a document is often organized in
tabular format to assist readers with information retrieval and comparison, which may be …

Tables are information-rich structured objects in document images. While significant work
has been done in localizing tables as graphic objects in document images, only limited …

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 …

We introduce a new table detection and structure recognition approach named
RobusTabNet to detect the boundaries of tables and reconstruct the cellular structure of …

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 …

A table arranging data in rows and columns is a very effective data structure, which has
been widely used in business and scientific research. Considering large-scale tabular data …

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 …

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 …