Table Detection
20 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 |
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ICDAR 2013
FUNSD
SciTSR
PubTables-1M
TableBank
IIIT-AR-13K
TNCR Dataset
ICDAR 2019
STDW
Latest papers
Table Detection for Visually Rich Document Images
Table Detection (TD) is a fundamental task to enable visually rich document understanding, which requires the model to extract information without information loss.
A large-scale dataset for end-to-end table recognition in the wild
To this end, we propose a new large-scale dataset named Table Recognition Set (TabRecSet) with diverse table forms sourcing from multiple scenarios in the wild, providing complete annotation dedicated to end-to-end TR research.
CTE: A Dataset for Contextualized Table Extraction
We define the task of Contextualized Table Extraction (CTE), which aims to extract and define the structure of tables considering the textual context of the document.
Deep learning for table detection and structure recognition: A survey
The goals of this survey are to provide a profound comprehension of the major developments in the field of Table Detection, offer insight into the different methodologies, and provide a systematic taxonomy of the different approaches.
Table Detection in the Wild: A Novel Diverse Table Detection Dataset and Method
In this paper, we introduce a diverse large-scale dataset for table detection with more than seven thousand samples containing a wide variety of table structures collected from many diverse sources.
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural Networks
Geometric Deep Learning has recently attracted significant interest in a wide range of machine learning fields, including document analysis.
DiT: Self-supervised Pre-training for Document Image Transformer
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.
PubTables-1M: Towards comprehensive table extraction from unstructured documents
microsoft/table-transformer
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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.
TableSense: Spreadsheet Table Detection with Convolutional Neural Networks
Spreadsheet table detection is the task of detecting all tables on a given sheet and locating their respective ranges.
TNCR: Table Net Detection and Classification Dataset
abdoelsayed2016/TNCR_Dataset
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Cascade Mask R-CNN with ResNeXt-101-64x4d Backbone Network achieves the highest performance compared to other methods with a precision of 79. 7%, recall of 89. 8%, and f1 score of 84. 4% on the TNCR dataset.
