Dear colleagues and researchers,
1st International workshop on Machine vision and NLP for Document Analysis (VINALDO)
As part of the 17th International Conference on Document Analysis and Recognition
August 21-26, 2023 — San José, California, USA
Document understanding is essential in various application areas such as data invoice extraction, subject review, medical prescription analysis, etc., and holds significant commercial potential. Several approaches are proposed in the literature, but datasets' availability and data privacy challenge it. Considering the problem of information extraction from documents, different aspects must be taken into account, such as (1) document classification, (2) text localization, (3) OCR (Optical Character Recognition), (4) table extraction, and (5) key information detection.
In this context, machine vision and, more precisely, deep learning models for image processing are attractive methods. In fact, several models for document analysis were developed for text box detection, text extraction, table extraction, etc. Different kinds of deep learning approaches, such as GNN, are used to tackle these tasks. On the other hand, the extracted text from documents can be represented using different embeddings based on recent NLP approaches such as Transformers. Also, understanding spatial relationships is critical for text document extraction results for some applications such as invoice analysis. Thus, the aim is to capture the structural connections between keywords (invoice number, date, amounts) and the main value (the desired information). An effective approach requires a combination of visual (spatial) and textual information.
The first edition of the machine VIsion and NAtural Language processing for DOcument analysis (VINALDO) workshop comes as an extension of the GLESDO workshop, where we encourage the description of novel problems or applications for document analysis in the area of information retrieval that has emerged in recent years. We also encourage works that include NLP tools for extracted text, such as language models and Transforms. Finally, we also encourage works that develop new scanned document datasets for novel applications.
The VINALDO workshop aims to bring together an area for industry, science, and academia experts to exchange ideas and discuss ongoing research in graph representation learning for scanned document analysis.
Topics of interests
We invite the submission of original works that are related -- but are not limited to -- the topics below:
Document structure and layout learning
OCR based methods
Semi-supervised methods for document analysis
Dynamic graph analysis
Information Retrieval and Extraction from documents
Knowledge graph for semantic document analysis
Semantic understanding of document content
Entity and link prediction in graphs
Merging ontologies with graph-based methods using NLP techniques
Cleansing and image enhancement techniques for scanned document
Font text recognition in a scanned document
Table identification and extraction from scanned documents
Handwriting detection and recognition in documents
Signature detection and verification in documents
Visual document structure understanding
Visual Question Answering
Scanned documents classification
Scanned documents summarization
Scanned documents translation
Graph-based approaches for a spatial component in a scanned document
Graph representation learning for NLP
The workshop is open to original papers of theoretical or practical nature. Papers should be formatted according to LNCS instructions for authors. VINALDO 2023 will follow a double-blind review process. Authors should not include their names and affiliations anywhere in the manuscript. Authors should also ensure that their identity is not revealed indirectly by citing their previous work in the third person and omitting acknowledgments until the camera-ready version. Papers have to be submitted via the workshop's EasyChair submission page.
We welcome the following types of contributions:
Full research papers (12-15 pages): Finished or consolidated R&D works to be included in one of the Workshop topics
Short papers (6-8 pages): ongoing works with relevant preliminary results, opened to discussion.
At least one author of each accepted paper must register for the workshop in order to present the paper. For further instructions, please refer to the ICDAR 2023 page.
Submission Deadline: March 17, 2023 at 11:59pm Pacific Time
Decisions Announced: April 17, 2023, at 11:59pm Pacific Time
Camera Ready Deadline: May 8, 2023, at 11:59pm Pacific Time
Workshop: August 24-26, 2023
Rim Hantach, Engie, France
Rafika Boutalbi, Aix-Marseille University, France