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Awesome Document Understanding

A curated list of resources for Document Understanding (DU) topic

1.5k stars180 forks89 entriesLast push Jun 2, 2023 (3 years ago)License none

This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.

General

Title of a publication / dataset / resource title

, [code/data/Website ]

In 6 listsDetails

Introduction >Papers

DocILE Benchmark for Document Information Localization and Extraction

, [Website] [benchmark] [code ]

Business Document Information Extraction: Towards Practical Benchmarks

Doc2Graph: A Task Agnostic Document Understanding Framework Based on Graph Neural Networks

, [code ]

Document AI: Benchmarks, Models and Applications

Efficient Automated Processing of the Unstructured Documents using Artificial Intelligence: A Systematic Literature…

A Survey of Deep Learning Approaches for OCR and Document Understanding

Conversations with Documents. An Exploration of Document-Centered Assistance

Future paradigms of automated processing of business documents

Machine Learning for Intelligent Processing of Printed Documents

Document Understanding: Research Directions

Resources

The RVL-CDIP Dataset

dataset consists of 400,000 grayscale images in 16 classes, with 25,000 images per class

The Industry Documents Library

a portal to millions of documents created by industries that influence public health, hosted by the UCSF Library

Color Document Dataset

from the Intelligent Sensory Information Systems, University of Amsterdam

The IIT CDIP Collection

dataset consists of documents from the states' lawsuit against the tobacco industry in the 1990s, consists of around 7 million documents

borb

is a pure python library to read, write and manipulate PDF documents. It represents a PDF document as a JSON-like datastructure of nested lists, dictionaries and primitives (numbers, string, booleans, etc).

pawls

PDF Annotations with Labels and Structure is software that makes it easy to collect a series of annotations associated with a PDF document

pdfplumber

Plumb a PDF for detailed information about each text character, rectangle, and line. Plus: Table extraction and visual debugging

In 2 lists

Pdfminer.six

Pdfminer.six is a community maintained fork of the original PDFMiner. It is a tool for extracting information from PDF documents. It focuses on getting and analyzing text data

In 3 lists

Layout Parser

Layout Parser is a deep learning based tool for document image layout analysis tasks

Tabulo

Table extraction from images

OCRmyPDF

OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched or copy-pasted

In 4 lists

PDFBox

The Apache PDFBox library is an open source Java tool for working with PDF documents. This project allows creation of new PDF documents, manipulation of existing documents and the ability to extract content from documents

In 2 lists

PdfPig

This project allows users to read and extract text and other content from PDF files. In addition the library can be used to create simple PDF documents containing text and geometrical shapes. This project aims to port PDFBox to C#

parsing-prickly-pdfs

Resources and worksheet for the NICAR 2016 workshop of the same name

pdf-text-extraction-benchmark

PDF tools benchmark

Born digital pdf scanner

checking if pdf is born-digital

OpenContracts

Apache2-licensed, PDF annotating platform for visually-rich documents that preserves the original layout and exports x,y positional data for tokens as well as span starts and stops. Based on PAWLs, but with a Python-based backend and readily deployable on your local machine, company intranet or…

deepdoctection

deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks for images and pdf documents using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and…

pydoxtools

Pydoxtools is an AI-composition library for dpocument analysis. It features an extensive toolset for building complex document analysis pipelines and recognizes most document formats out of the box. It supports typical NLP tasks such as keywords, summarization, question_answering out of the box.…

Conferences, workshops

ACM International Conference on AI in Finance (ICAIF)

The AAAI-21 Workshop on Knowledge Discovery from Unstructured Data in Financial Services

CVPR 2020 Workshop on Text and Documents in the Deep Learning Era

KDD Workshop on Machine Learning in Finance (KDD MLF 2020)

FinIR 2020: The First Workshop on Information Retrieval in Finance

2nd KDD Workshop on Anomaly Detection in Finance (KDD 2019)

Document Understanding Conference (DUC 2007)

The AAAI-21 Workshop on Scientific Document Understanding (SDU 2021)

First Workshop on Scholarly Document Processing (SDProc 2020)

Blogs

A Survey of Document Understanding Models

, 2021

Document Form Extraction

, 2021

How to automate processes with unstructured data

, 2021

A Comprehensive Guide to OCR with RPA and Document Understanding

, 2021

Information Extraction from Receipts with Graph Convolutional Networks

, 2021

How to extract structured data from invoices

, 2021

Extracting Structured Data from Templatic Documents

, 2020

To apply AI for good, think form extraction

, 2020

UiPath Document Understanding Solution Architecture and Approach

, 2020

How Can I Automate Data Extraction from Complex Documents?

, 2020

LegalTech: Information Extraction in legal documents

, 2020

Solutions

Abby

Accenture

Amazon

Google

Microsoft

The Microsoft Azure Machine Learning platform provides capabilities such as natural language processing, recommendation engine, pattern recognition, computer vision, and predictive modeling.

In 2 lists

Uipath

Applica.ai

Base64.ai

Docstack

Element AI

Indico

Instabase

Konfuzio

team-first hosted and on-prem text, image and PDF annotation tool powered by active learning, freemium based, costs $

In 3 lists

Metamaze

Nanonets

Rossum

Silo

Inspirations

https://github.com/kba/awesome-ocr

This list contains links to great software tools and libraries and literature related to Optical Character Recognition (OCR).

In 4 lists

https://github.com/Liquid-Legal-Institute/Legal-Text-Analytics

https://github.com/icoxfog417/awesome-financial-nlp

https://github.com/BobLd/DocumentLayoutAnalysis

https://github.com/bikash/DocumentUnderstanding

https://github.com/harpribot/awesome-information-retrieval

Information retrieval resources

In 3 listsDetails

https://github.com/roomylee/awesome-relation-extraction

https://github.com/caufieldjh/awesome-bioie

https://github.com/HelloRusk/entity-related-papers

https://github.com/pliang279/awesome-multimodal-ml

In 2 lists

https://github.com/thunlp/LegalPapers

https://github.com/heartexlabs/awesome-data-labeling

https://github.com/jsbroks/awesome-dataset-tools

https://github.com/EthicalML/awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

In 5 listsDetails

https://github.com/eugeneyan/applied-ml

Curated resources and tools for applied machine learning in industry.

In 6 listsDetails

https://github.com/awesomedata/awesome-public-datasets

An awesome repository full of open datasets from an abundance of different categories.

In 9 listsDetails

https://github.com/keon/awesome-nlp

A ranked list of awesome Python libraries for natural language processing (NLP).

In 6 listsDetails

https://github.com/thunlp/PLMpapers

BERT (Transformer, transfer learning) has catalyzed research in pretrained language models (PLMs) and has sparked many extensions. This repo contains a list of papers on PLMs.

In 2 lists

https://github.com/jbhuang0604/awesome-computer-vision#awesome-lists

컴퓨터 비전 자료모음 (Awesome 계열)

In 7 listsDetails

https://github.com/papers-we-love/papers-we-love

“The practice of software engineering, and its history is, itself, a complex study in humanity, coordination, and communication.”

In 8 listsDetails

https://github.com/BAILOOL/DoYouEvenLearn

https://github.com/hibayesian/awesome-automl-papers

In 2 lists
See category
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