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- surveyApril 2024JUST ACCEPTED
Deep Learning for Table Detection and Structure Recognition: A Survey
- Mahmoud Kasem,
- Abdelrahman Abdallah,
- Alexander Berendeyev,
- Ebrahem Elkady,
- Mohamed Mahmoud,
- Mahmoud Abdalla,
- Mohamed Hamada,
- Sebastiano Vascon,
- Daniyar Nurseitov,
- Islam Taj-Eddin
Tables are everywhere, from scientific journals, papers, websites, and newspapers all the way to items we buy at the supermarket. Detecting them is thus of utmost importance to automatically understanding the content of a document. The performance of ...
- research-articleOctober 2023
TC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content
- Avinash Anand,
- Raj Jaiswal,
- Pijush Bhuyan,
- Mohit Gupta,
- Siddhesh Bangar,
- Md. Modassir Imam,
- Rajiv Ratn Shah,
- Shin'ichi Satoh
MMIR '23: Proceedings of the 1st International Workshop on Deep Multimodal Learning for Information RetrievalNovember 2023, Pages 11–18https://doi.org/10.1145/3606040.3617444The automatic recognition of tabular data in document images presents a significant challenge due to the diverse range of table styles and complex structures. Tables offer valuable content representation, enhancing the predictive capabilities of various ...
- ArticleAugust 2023
PyramidTabNet: Transformer-Based Table Recognition in Image-Based Documents
Document Analysis and Recognition - ICDAR 2023Aug 2023, Pages 420–437https://doi.org/10.1007/978-3-031-41734-4_26AbstractTable detection and structure recognition is an important component of document analysis systems. Deep learning-based transformer models have recently demonstrated significant success in various computer vision and document analysis tasks. In this ...
- research-articleOctober 2022
DiT: Self-supervised Pre-training for Document Image Transformer
MM '22: Proceedings of the 30th ACM International Conference on MultimediaOctober 2022, Pages 3530–3539https://doi.org/10.1145/3503161.3547911Image Transformer has recently achieved significant progress for natural image understanding, either using supervised (ViT, DeiT, etc.) or self-supervised (BEiT, MAE, etc.) pre-training techniques. In this paper, we propose DiT, a self-supervised pre-...
- short-paperAugust 2021
Rescuing historical climate observations to support hydrological research: a case study of solar radiation data
- Ogundepo Odunayo,
- Naveela N. Sookoo,
- Gautam Bathla,
- Anthony Cavallin,
- Bhaleka D. Persaud,
- Kathy Szigeti,
- Philippe Van Cappellen,
- Jimmy Lin
DocEng '21: Proceedings of the 21st ACM Symposium on Document EngineeringAugust 2021, Article No.: 19, Pages 1–4https://doi.org/10.1145/3469096.3474929The acceleration of climate change and its impact highlight the need for long-term reliable climate data at high spatiotemporal resolution to answer key science questions in cold regions hydrology. Prior to the digital age, climate records were archived ...
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- research-articleMay 2021
Table detection and cell segmentation in online handwritten documents with graph attention networks
MMAsia '20: Proceedings of the 2nd ACM International Conference on Multimedia in AsiaMarch 2021, Article No.: 42, Pages 1–6https://doi.org/10.1145/3444685.3446295In this paper, we propose a multi-task learning approach for table detection and cell segmentation with densely connected graph attention networks in free form online documents. Each online document is regarded as a graph, where nodes represent strokes ...
- research-articleFebruary 2018
Learning to detect tables in document images using line and text information
ICMLSC '18: Proceedings of the 2nd International Conference on Machine Learning and Soft ComputingFebruary 2018, Pages 151–155https://doi.org/10.1145/3184066.3184091Table detection is a crucial step in many document analysis applications as tables are used for presenting essential information to readers in a structured manner. It is still a challenging problem due to the variety of table structures and the ...
- abstractSeptember 2016
Table Modelling, Extraction and Processing
DocEng '16: Proceedings of the 2016 ACM Symposium on Document EngineeringSeptember 2016, Pages 1–2https://doi.org/10.1145/2960811.2967173This tutorial is targeted at academics and practitioners, both within and outside of the Document Engineering community, who are confronted with table processing tasks such as information extraction and conversion, or have an interest in the topic, and ...
- research-articleDecember 2012
Model based table cell detection and content extraction from degraded document images
DAR '12: Proceeding of the workshop on Document Analysis and RecognitionDecember 2012, Pages 62–67https://doi.org/10.1145/2432553.2432565This paper describes a novel method for detection and extraction of contents of table cells from handwritten document images. Given a model of the table and a document image containing a table, the hand-drawn or pre-printed table is detected and the ...
- research-articleDecember 2012
Table detection in document images using header and trailer patterns
ICVGIP '12: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image ProcessingDecember 2012, Article No.: 62, Pages 1–8https://doi.org/10.1145/2425333.2425395This paper presents a new approach to detect tabular structures present in document images and in low resolution video images. The algorithm for table detection is based on identifying the unique table start pattern and table trailer pattern. We have ...
- ArticleMarch 2012
Dataset, Ground-Truth and Performance Metrics for Table Detection Evaluation
DAS '12: Proceedings of the 2012 10th IAPR International Workshop on Document Analysis SystemsMarch 2012, Pages 445–449https://doi.org/10.1109/DAS.2012.29Table detection is an important task in the field of document analysis. It has been extensively studied since a couple of decades. Various kinds of document mediums are involved, from scanned images to web pages, from plain texts to PDF files. Numerous ...
- ArticleSeptember 2011
Table Detection in Noisy Off-line Handwritten Documents
ICDAR '11: Proceedings of the 2011 International Conference on Document Analysis and RecognitionSeptember 2011, Pages 399–403https://doi.org/10.1109/ICDAR.2011.88Table detection can be a valuable step in the analysis of unstructured documents. Although much work has been conducted in the domain of machine-print including books, scientific papers, etc., little has been done to address the case of handwritten ...
- ArticleSeptember 2011
A Table Detection Method for Multipage PDF Documents via Visual Seperators and Tabular Structures
ICDAR '11: Proceedings of the 2011 International Conference on Document Analysis and RecognitionSeptember 2011, Pages 779–783https://doi.org/10.1109/ICDAR.2011.304Table detection is always an important task of document analysis and recognition. In this paper, we propose a novel and effective table detection method via visual separators and geometric content layout information, targeting at PDF documents. The ...
- posterSeptember 2010
Towards a common evaluation strategy for table structure recognition algorithms
DocEng '10: Proceedings of the 10th ACM symposium on Document engineeringSeptember 2010, Pages 255–258https://doi.org/10.1145/1860559.1860617A number of methods for evaluating table structure recognition systems have been proposed in the literature, which have been used successfully for automatic and manual optimization of their respective algorithms. Unfortunately, the lack of standard, ...
- research-articleJune 2010
Table detection in heterogeneous documents
DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis SystemsJune 2010, Pages 65–72https://doi.org/10.1145/1815330.1815339Detecting tables in document images is important since not only do tables contain important information, but also most of the layout analysis methods fail in the presence of tables in the document image. Existing approaches for table detection mainly ...
- ArticleSeptember 2008
A Fast Preprocessing Method for Table Boundary Detection: Narrowing Down the Sparse Lines Using Solely Coordinate Information
DAS '08: Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis SystemsSeptember 2008, Pages 431–438https://doi.org/10.1109/DAS.2008.77As the rapid growth of PDF document in digital libraries, recognizing the document structure and detecting specific document components are useful for document storage, classification and retrieval. Tables, as a specific document component, are ...
- ArticleJune 2006
Automatic extraction of table metadata from digital documents
JCDL '06: Proceedings of the 6th ACM/IEEE-CS joint conference on Digital librariesJune 2006, Pages 339–340https://doi.org/10.1145/1141753.1141835Tables are used to present, list, summarize, and structure important data in documents. In scholarly articles, they are often used to present the relationships among data and high-light a collection of results obtained from experiments and scientific ...
- ArticleMay 2006
Visually guided bottom-up table detection and segmentation in web documents
WWW '06: Proceedings of the 15th international conference on World Wide WebMay 2006, Pages 933–934https://doi.org/10.1145/1135777.1135951In the AllRight project, we are developing an algorithm for unsupervised table detection and segmentation that uses the visual rendition of a Web page rather than the HTML code. Our algorithm works bottom-up by grouping word bounding boxes into larger ...
- ArticleApril 2006
Detection and segmentation of tables and math-zones from document images
SAC '06: Proceedings of the 2006 ACM symposium on Applied computingApril 2006, Pages 841–846https://doi.org/10.1145/1141277.1141469We propose an algorithm to separate out tables and math-zones from document images. The algorithm relies on the spatial characteristics of tables and math-zones in a document. It has been observed that tables have distinct columns which imply that gaps ...
- ArticleMay 2005
Using visual cues for extraction of tabular data from arbitrary HTML documents
WWW '05: Special interest tracks and posters of the 14th international conference on World Wide WebMay 2005, Pages 1000–1001https://doi.org/10.1145/1062745.1062838We describe a method to extract tabular data from web pages. Rather than just analyzing the DOM tree, we also exploit visual cues in the rendered version of the document to extract data from tables which are not explicitly marked with an HTML table ...