Current status and performance analysis of table recognition in document images with deep neural networks
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 …
Subsequently, the tabular structures are recognized in the second phase in order to extract …
Deep learning for table detection and structure recognition: A survey
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 …
way to items we buy at the supermarket. Detecting them is thus of utmost importance to …
Tabbie: Pretrained representations of tabular data
Existing work on tabular representation learning jointly models tables and associated text
using self-supervised objective functions derived from pretrained language models such as …
using self-supervised objective functions derived from pretrained language models such as …
Image-based table recognition: data, model, and evaluation
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 …
tabular format to assist readers with information retrieval and comparison, which may be …
Table structure recognition using top-down and bottom-up cues
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 …
has been done in localizing tables as graphic objects in document images, only limited …
Global table extractor (gte): A framework for joint table identification and cell structure recognition using visual context
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 …
business and science, within which are tables that capture most of the critical data …
Lgpma: Complicated table structure recognition with local and global pyramid mask alignment
Table structure recognition is a challenging task due to the various structures and
complicated cell spanning relations. Previous methods handled the problem starting from …
complicated cell spanning relations. Previous methods handled the problem starting from …
Improving table structure recognition with visual-alignment sequential coordinate modeling
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 …
table images into a machine-readable format. The latest end-to-end image-to-text …
Robust table detection and structure recognition from heterogeneous document images
We introduce a new table detection and structure recognition approach named
RobusTabNet to detect the boundaries of tables and reconstruct the cellular structure of …
RobusTabNet to detect the boundaries of tables and reconstruct the cellular structure of …
Structextv2: Masked visual-textual prediction for document image pre-training
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 …
by performing masked visual-textual prediction. It consists of two self-supervised pre-training …