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Found 6 papers, 4 papers with code
OCR-free Document Understanding Transformer
Current Visual Document Understanding (VDU) methods outsource the task of reading text to off-the-shelf Optical Character Recognition (OCR) engines and focus on the understanding task with the OCR outputs.
Ranked #10 on
Document Image Classification
on RVL-CDIP
Cost-effective End-to-end Information Extraction for Semi-structured Document Images
A real-world information extraction (IE) system for semi-structured document images often involves a long pipeline of multiple modules, whose complexity dramatically increases its development and maintenance cost.
Syntactic Question Abstraction and Retrieval for Data-Scarce Semantic Parsing
Deep learning approaches to semantic parsing require a large amount of labeled data, but annotating complex logical forms is costly.
Spatial Dependency Parsing for Semi-Structured Document Information Extraction
Information Extraction (IE) for semi-structured document images is often approached as a sequence tagging problem by classifying each recognized input token into one of the IOB (Inside, Outside, and Beginning) categories.
Post-OCR parsing: building simple and robust parser via BIO tagging
Parsing textual information embedded in images is important for various down- stream tasks.
Optical Character Recognition
Optical Character Recognition (OCR)
A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization
We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset.
