Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)
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Updated
Oct 31, 2022 - Python
Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)
This small module connects Label Studio with Fonduer by creating a fonduer labeling function for gold labels from a label studio export. Documentation: https://irgroup.github.io/labelstudio-to-fonduer/
Implementation of the paper: Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer.
Doc2Graph transforms documents into graphs and exploit a GNN to solve several tasks.
A curated list of resources for Document Understanding (DU) topic
(WIP) ✨ A comprehensive resource for understanding the world of software used in the Document Understanding field. 🧙✨
QuickCapture Mobile Scanning SDK Specially designed for native IOS
This project tackles a real-world challenge of automating client document processing, with a focus on enhancing document classification, error detection, data extraction, and validation.
Object Detection Model for Scanned Documents
A hands-on CLI tool sample showcasing the integration of Dart with Google Cloud's DocumentAI.
Checkbox Detection Model for Scanned Documents
TAT-DQA: Towards Complex Document Understanding By Discrete Reasoning
QuickCapture Mobile Scanning SDK Specially designed for native ANDROID from Extrieve
Official release of RFUND introduced in the paper "PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair Extraction" (arXiv:2401.03472).
Datasets and Evaluation Scripts for CompHRDoc
Minimal sharded dataset loaders, decoders, and utils for multi-modal document, image, and text datasets.
Run optical character recognition with PyTesseract from the FiftyOne App!
A collection of original, innovative ideas and algorithms towards Advanced Literate Machinery. This project is maintained by the OCR Team in the Language Technology Lab, Tongyi Lab, Alibaba Group.
Code for the paper "PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks" (ICPR 2020)
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