Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
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Updated
Dec 15, 2024 - Python
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022
A Repo For Document AI
A curated list of resources for Document Understanding (DU) topic
Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)
Algorithms, papers, datasets, performance comparisons for Document AI. Continuously updating.
Official Implementation of Web-based Visual Corpus Builder (Webvicob), ICDAR 2023
ReadingBank: A Benchmark Dataset for Reading Order Detection
SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images (AAAI2023)
An unofficial PyTorch implementation of "Lin et al. ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents. ICDAR, 2021"
Table detection (TD) and table structure recognition (TSR) using Yolov5/Yolov8, and you can get the same (even better) result compared with Table Transformer (TATR) with smaller models.
This repository includes all computer vision, audio, document AI, and multimodal projects.
Document AI Toolbox is an SDK for Python that provides utility functions for managing, manipulating, and extracting information from the document response. It creates a "wrapped" document object from JSON files in Cloud Storage, local JSON files, or output directly from the Document AI API.
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
[MM'2024] PEneo, an effective algorithm for key-value pair extraction from form-like documents, designed for real-world applications.
[MM'2024] Official release of RFUND introduced in the MM'2024 paper "PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair Extraction"
[Paper] Code for the EMNLP2023 (Findings) paper "Global Structure Knowledge-Guided Relation Extraction Method for Visually-Rich Document"
(WIP) ✨ A comprehensive resource for understanding the world of software used in the Document Understanding field. 🧙✨
A hands-on CLI tool sample showcasing the integration of Dart with Google Cloud's DocumentAI.
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