| |
Records |
Links |
|
Author |
Pau Riba; Lutz Goldmann; Oriol Ramos Terrades; Diede Rusticus; Alicia Fornes; Josep Llados |
|
| |
Title |
Table detection in business document images by message passing networks |
Type |
Journal Article |
| |
Year |
2022 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
| |
Volume |
127 |
Issue |
|
Pages |
108641 |
|
| |
Keywords |
|
|
| |
Abstract |
Tabular structures in business documents offer a complementary dimension to the raw textual data. For instance, there is information about the relationships among pieces of information. Nowadays, digital mailroom applications have become a key service for workflow automation. Therefore, the detection and interpretation of tables is crucial. With the recent advances in information extraction, table detection and recognition has gained interest in document image analysis, in particular, with the absence of rule lines and unknown information about rows and columns. However, business documents usually contain sensitive contents limiting the amount of public benchmarking datasets. In this paper, we propose a graph-based approach for detecting tables in document images which do not require the raw content of the document. Hence, the sensitive content can be previously removed and, instead of using the raw image or textual content, we propose a purely structural approach to keep sensitive data anonymous. Our framework uses graph neural networks (GNNs) to describe the local repetitive structures that constitute a table. In particular, our main application domain are business documents. We have carefully validated our approach in two invoice datasets and a modern document benchmark. Our experiments demonstrate that tables can be detected by purely structural approaches. |
|
| |
Address |
July 2022 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Elsevier |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.162; 600.121 |
Approved |
no |
|
| |
Call Number  |
Admin @ si @ |
Serial |
3729 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
|
| |
Title |
16th International Conference, 2021, Proceedings, Part III |
Type |
Book Whole |
| |
Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
Abbreviated Journal |
|
|
| |
Volume |
12823 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
|
| |
Address |
Lausanne, Switzerland, September 5-10, 2021 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Cham |
Place of Publication |
|
Editor |
Josep Llados; Daniel Lopresti; Seiichi Uchida |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-030-86333-3 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3727 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
|
| |
Title |
16th International Conference, 2021, Proceedings, Part IV |
Type |
Book Whole |
| |
Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
Abbreviated Journal |
|
|
| |
Volume |
12824 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
|
| |
Address |
Lausanne, Switzerland, September 5-10, 2021 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Cham |
Place of Publication |
|
Editor |
Josep Llados; Daniel Lopresti; Seiichi Uchida |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-030-86336-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3728 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mohamed Ali Souibgui; Asma Bensalah; Jialuo Chen; Alicia Fornes; Michelle Waldispühl |
|
| |
Title |
A User Perspective on HTR methods for the Automatic Transcription of Rare Scripts: The Case of Codex Runicus Just Accepted |
Type |
Journal Article |
| |
Year |
2022 |
Publication |
ACM Journal on Computing and Cultural Heritage |
Abbreviated Journal |
JOCCH |
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Recent breakthroughs in Artificial Intelligence, Deep Learning and Document Image Analysis and Recognition have significantly eased the creation of digital libraries and the transcription of historical documents. However, for documents in rare scripts with few labelled training data available, current Handwritten Text Recognition (HTR) systems are too constraint. Moreover, research on HTR often focuses on technical aspects only, and rarely puts emphasis on implementing software tools for scholars in Humanities. In this article, we describe, compare and analyse different transcription methods for rare scripts. We evaluate their performance in a real use case of a medieval manuscript written in the runic script (Codex Runicus) and discuss advantages and disadvantages of each method from the user perspective. From this exhaustive analysis and comparison with a fully manual transcription, we raise conclusions and provide recommendations to scholars interested in using automatic transcription tools. |
|
| |
Address |
July 2022 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
ACM |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.121; 600.162; 602.230; 600.140 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3732 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
|
| |
Title |
16th International Conference, 2021, Proceedings, Part I |
Type |
Book Whole |
| |
Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
Abbreviated Journal |
|
|
| |
Volume |
12821 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: historical document analysis, document analysis systems, handwriting recognition, scene text detection and recognition, document image processing, natural language processing (NLP) for document understanding, and graphics, diagram and math recognition. |
|
| |
Address |
Lausanne, Switzerland, September 5-10, 2021 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Cham |
Place of Publication |
|
Editor |
Josep Llados; Daniel Lopresti; Seiichi Uchida |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-030-86548-1 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3725 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
|
| |
Title |
16th International Conference, 2021, Proceedings, Part II |
Type |
Book Whole |
| |
Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
Abbreviated Journal |
|
|
| |
Volume |
12822 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
|
| |
Address |
Lausanne, Switzerland, September 5-10, 2021 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Cham |
Place of Publication |
|
Editor |
Josep Llados; Daniel Lopresti; Seiichi Uchida |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-030-86330-2 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3726 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados |
|
| |
Title |
The 5G of Document Intelligence |
Type |
Conference Article |
| |
Year |
2021 |
Publication |
3rd Workshop on Future of Document Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Lausanne; Suissa; September 2021 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
FDAR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3677 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mohamed Ali Souibgui; Sanket Biswas; Sana Khamekhem Jemni; Yousri Kessentini; Alicia Fornes; Josep Llados; Umapada Pal |
|
| |
Title |
DocEnTr: An End-to-End Document Image Enhancement Transformer |
Type |
Conference Article |
| |
Year |
2022 |
Publication |
26th International Conference on Pattern Recognition (ICPR) |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1699-1705 |
|
| |
Keywords |
|
|
| |
Abstract |
Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for proper usage. To address this challenge, we present a new encoder-decoder architecture based on vision transformers to enhance both machine-printed and handwritten document images, in an end-to-end fashion. The encoder operates directly on the pixel patches with their positional information without the use of any convolutional layers, while the decoder reconstructs a clean image from the encoded patches. Conducted experiments show a superiority of the proposed model compared to the state-of the-art methods on several DIBCO benchmarks. Code and models will be publicly available at: https://github.com/dali92002/DocEnTR |
|
| |
Address |
August 21-25, 2022 , Montréal Québec |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
DAG; 600.121; 600.162; 602.230; 600.140 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3730 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados |
|
| |
Title |
A Generic Image Retrieval Method for Date Estimation of Historical Document Collections |
Type |
Conference Article |
| |
Year |
2022 |
Publication |
Document Analysis Systems.15th IAPR International Workshop, (DAS2022) |
Abbreviated Journal |
|
|
| |
Volume |
13237 |
Issue |
|
Pages |
583–597 |
|
| |
Keywords |
Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG |
|
| |
Abstract |
Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images. |
|
| |
Address |
La Rochelle, France; May 22–25, 2022 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
DAS |
|
| |
Notes |
DAG; 600.140; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3694 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Brugues Pujolras; Lluis Gomez; Dimosthenis Karatzas |
|
| |
Title |
A Multilingual Approach to Scene Text Visual Question Answering |
Type |
Conference Article |
| |
Year |
2022 |
Publication |
Document Analysis Systems.15th IAPR International Workshop, (DAS2022) |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
65-79 |
|
| |
Keywords |
Scene text; Visual question answering; Multilingual word embeddings; Vision and language; Deep learning |
|
| |
Abstract |
Scene Text Visual Question Answering (ST-VQA) has recently emerged as a hot research topic in Computer Vision. Current ST-VQA models have a big potential for many types of applications but lack the ability to perform well on more than one language at a time due to the lack of multilingual data, as well as the use of monolingual word embeddings for training. In this work, we explore the possibility to obtain bilingual and multilingual VQA models. In that regard, we use an already established VQA model that uses monolingual word embeddings as part of its pipeline and substitute them by FastText and BPEmb multilingual word embeddings that have been aligned to English. Our experiments demonstrate that it is possible to obtain bilingual and multilingual VQA models with a minimal loss in performance in languages not used during training, as well as a multilingual model trained in multiple languages that match the performance of the respective monolingual baselines. |
|
| |
Address |
La Rochelle, France; May 22–25, 2022 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
DAS |
|
| |
Notes |
DAG; 611.004; 600.155; 601.002 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3695 |
|
| Permanent link to this record |
