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 …

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

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

Multimodal learning from document data has achieved great success lately as it allows to
pre-train semantically meaningful features as a prior into a learnable downstream task. In …

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 …

Table structure recognition (TSR) aims at extracting tables in images into machine-
understandable formats. Current approaches address this issue by either predicting the …

Billions of documents in data sheet format are shared between various organizations across
the globe on a daily basis. The essential information in these documents is presented in …

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