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20202025
most citedA Large Dataset of Historical Japanese Documents with Complex Layouts

3 citations · 3 across the 1 of their papers we have counts for

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cs.CV2023

EfficientOCR: An Extensible, Open-Source Package for Efficiently Digitizing World Knowledge

Tom Bryan, Jacob Carlson, Abhishek Arora +1

Billions of public domain documents remain trapped in hard copy or lack an accurate digitization. Modern natural language processing methods cannot be used to index, retrieve, and…

cs.CV2023

Linking Representations with Multimodal Contrastive Learning

Abhishek Arora, Xinmei Yang, Shao-Yu Jheng +1

Many applications require linking individuals, firms, or locations across datasets. Most widely used methods, especially in social science, do not employ deep learning, with record…

cs.CV2023

Efficient OCR for Building a Diverse Digital History

Jacob Carlson, Tom Bryan, Melissa Dell

Thousands of users consult digital archives daily, but the information they can access is unrepresentative of the diversity of documentary history. The sequence-to-sequence archite…

cs.CV2021

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

Zejiang Shen, Ruochen Zhang, Melissa Dell +3

Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production…

cs.CV20203 cited

A Large Dataset of Historical Japanese Documents with Complex Layouts

Zejiang Shen, Kaixuan Zhang, Melissa Dell

Deep learning-based approaches for automatic document layout analysis and content extraction have the potential to unlock rich information trapped in historical documents on a larg…