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Attention where it matters: Rethinking visual document understanding with selective region concentration
We propose a novel end-to-end document understanding model called SeRum (SElective
Region Understanding Model) for extracting meaningful information from document images …
Region Understanding Model) for extracting meaningful information from document images …
You can even annotate text with voice: Transcription-only-supervised text spotting
End-to-end scene text spotting has recently gained great attention in the research
community. The majority of existing methods rely heavily on the location annotations of text …
community. The majority of existing methods rely heavily on the location annotations of text …
Filling in the blank: Rationale-augmented prompt tuning for TextVQA
Recently, generative Text-based visual question answering (TextVQA) methods, which are
often based on language models, have exhibited impressive results and drawn increasing …
often based on language models, have exhibited impressive results and drawn increasing …
ICDAR 2023 competition on structured text extraction from visually-rich document images
Structured text extraction is one of the most valuable and challenging application directions
in the field of Document AI. However, the scenarios of past benchmarks are limited, and the …
in the field of Document AI. However, the scenarios of past benchmarks are limited, and the …
Query-driven generative network for document information extraction in the wild
This paper focuses on solving Document Information Extraction (DIE) in the wild problem,
which is rarely explored before. In contrast to existing studies mainly tailored for document …
which is rarely explored before. In contrast to existing studies mainly tailored for document …
Lapdoc: Layout-aware prompting for documents
Recent advances in training large language models (LLMs) using massive amounts of
solely textual data lead to strong generalization across many domains and tasks, including …
solely textual data lead to strong generalization across many domains and tasks, including …
Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review
Extracting key information from documents represents a large portion of business workloads
and therefore offers a high potential for efficiency improvements and process automation …
and therefore offers a high potential for efficiency improvements and process automation …
Document information extraction via global tagging
Abstract Document Information Extraction (DIE) is a crucial task for extracting key information
from visually-rich documents. The typical pipeline approach for this task involves Optical …
from visually-rich documents. The typical pipeline approach for this task involves Optical …
GenTC: Generative Transformer via Contrastive Learning for Receipt Information Extraction
X Deng, Z Huang, K Ma, K Chen, J Guo… - … Conference on Artificial …, 2023 - Springer
Abstract Information Extraction from visually rich documents has attracted increasing
attention due to its various advanced applications in the real world. Most existing methods …
attention due to its various advanced applications in the real world. Most existing methods …
First-place Solution for Streetscape Shop Sign Recognition Competition
B Wang, L **g - arxiv preprint arxiv:2501.02811, 2025 - arxiv.org
Text recognition technology applied to street-view storefront signs is increasingly utilized
across various practical domains, including map navigation, smart city planning analysis …
across various practical domains, including map navigation, smart city planning analysis …