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 …

This paper presents a novel end-to-end system for table understanding in document images
called DeepDeSRT. In particular, the contribution of DeepDeSRT is two-fold. First, it …

Tables are probably the most natural way to represent relational data in various media and
formats. They store a large number of valuable facts that could be utilized for question …

With the widespread use of mobile phones and scanners to photograph and upload
documents, the need for extracting the information trapped in unstructured document images …

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 …

Documents are often the format of choice for knowledge sharing and preservation in
business and science, within which are tables that capture most of the critical data …

Table structure recognition is a challenging task due to the various structures and
complicated cell spanning relations. Previous methods handled the problem starting from …

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

This paper tackles the problem of table structure pars-ing (TSP) from images in the wild. In
contrast to existingstudies that mainly focus on parsing well-aligned tabularimages with …

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 …