Table Detection
19 papers with code • 3 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Table Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
ICDAR 2013
FUNSD
SciTSR
TableBank
PubTables-1M
IIIT-AR-13K
TNCR Dataset
cTDaR
STDW
Most implemented papers
TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images
This includes accurate detection of the tabular region within an image, and subsequently detecting and extracting information from the rows and columns of the detected table.
CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents
DevashishPrasad/CascadeTabNet
•
•
In this paper, we present an improved deep learning-based end to end approach for solving both problems of table detection and structure recognition using a single Convolution Neural Network (CNN) model.
DiT: Self-supervised Pre-training for Document Image Transformer
microsoft/unilm
•
•
We leverage DiT as the backbone network in a variety of vision-based Document AI tasks, including document image classification, document layout analysis, table detection as well as text detection for OCR.
TableBank: A Benchmark Dataset for Table Detection and Recognition
We present TableBank, a new image-based table detection and recognition dataset built with novel weak supervision from Word and Latex documents on the internet.
Table understanding in structured documents
Darthholi/similarity-models
•
•
We will work on our newly presented dataset of pro forma invoices, invoices and debit note documents using this representation and propose multiple baselines to solve this labeling problem.
CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images
mdv3101/CDeCNet
•
•
Localizing page elements/objects such as tables, figures, equations, etc.
PubTables-1M: Towards comprehensive table extraction from unstructured documents
microsoft/table-transformer
•
•
CVPR 2022
We demonstrate that these improvements lead to a significant increase in training performance and a more reliable estimate of model performance at evaluation for table structure recognition.
A framework for information extraction from tables in biomedical literature
The scientific literature is growing exponentially, and professionals are no more able to cope with the current amount of publications.
The Benefits of Close-Domain Fine-Tuning for Table Detection in Document Images
A correct localisation of tables in a document is instrumental for determining their structure and extracting their contents; therefore, table detection is a key step in table understanding.
TableBank: Table Benchmark for Image-based Table Detection and Recognition
We present TableBank, a new image-based table detection and recognition dataset built with novel weak supervision from Word and Latex documents on the internet.
