Papers Table Detection
“Table Detection” 태그가 달린 논문 64편 · 필터 해제
Structured Prediction for Scalable Spreadsheet Table Understanding: From Cell Types to Table Ranges (Extended Version)
Spreadsheets are a primary medium for publishing tabular data, yet automatically extracting structured content from them remains difficult due to heterogeneous layouts, diverse file formats, and inconsistent organization…
Structured PredictionTable DetectionActive Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines
Table extraction from business documents relies on a cascaded pipeline where Table Detection (TD) first localizes tables and Table Structure Recognition (TSR) then recovers their internal layout. Building task-specific t…
Image ClassificationObject DetectionTable DetectionActive LearningLow-Resource Heuristics for Bahnaric Optical Character Recognition Improvement
Bahnar, a minority language spoken across Vietnam, Cambodia, and Laos, faces significant preservation challenges due to limited research and data availability. This study addresses the critical need for accurate digitiza…
Information RetrievalTable DetectionTable Detection with Active Learning
Efficient data annotation remains a critical challenge in machine learning, particularly for object detection tasks requiring extensive labeled data. Active learning (AL) has emerged as a promising solution to minimize a…
Object DetectionActive LearningTable DetectionTASER: Table Agents for Schema-guided Extraction and Recommendation
Real-world financial filings report critical information about an entity's investment holdings, essential for assessing that entity's risk, profitability, and relationship profile. Yet, these details are often buried in …
Table DetectionFrom Surface to Semantics: Semantic Structure Parsing for Table-Centric Document Analysis
Documents are core carriers of information and knowl-edge, with broad applications in finance, healthcare, and scientific research. Tables, as the main medium for structured data, encapsulate key information and are amon…
Semantic ParsingTable RetrievalTable DetectionSynthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images
Document pages captured by smartphones or scanners often contain tables, yet manual extraction is slow and error-prone. We introduce an automated LaTeX-based pipeline that synthesizes realistic two-column pages with visu…
Data AugmentationTable DetectionCreating a Historical Migration Dataset from Finnish Church Records, 1800-1920
This article presents a large-scale effort to create a structured dataset of internal migration in Finland between 1800 and 1920 using digitized church moving records. These records, maintained by Evangelical-Lutheran pa…
Handwriting RecognitionTable DetectionUniHDSA: A Unified Relation Prediction Approach for Hierarchical Document Structure Analysis
Document structure analysis, aka document layout analysis, is crucial for understanding both the physical layout and logical structure of documents, serving information retrieval, document summarization, knowledge extrac…
Document Layout AnalysisDocument SummarizationInformation RetrievalPrediction+3RAPTOR: Refined Approach for Product Table Object Recognition
Extracting tables from documents is a critical task across various industries, especially on business documents like invoices and reports. Existing systems based on DEtection TRansformer (DETR) such as TAble TRansformer …
ObjectObject RecognitionTable DetectionTable ExtractionCISOL: An Open and Extensible Dataset for Table Structure Recognition in the Construction Industry
Reproducibility and replicability are critical pillars of empirical research, particularly in machine learning, where they depend not only on the availability of models, but also on the datasets used to train and evaluat…
BenchmarkingObject DetectionTable DetectionTable ExtractionTabSniper: Towards Accurate Table Detection & Structure Recognition for Bank Statements
Extraction of transaction information from bank statements is required to assess one's financial well-being for credit rating and underwriting decisions. Unlike other financial documents such as tax forms or financial st…
Table DetectionA Comparative Study of PDF Parsing Tools Across Diverse Document Categories
PDF is one of the most prominent data formats, making PDF parsing crucial for information extraction and retrieval, particularly with the rise of RAG systems. While various PDF parsing tools exist, their effectiveness ac…
RAGTable DetectionSpreadsheetLLM: Encoding Spreadsheets for Large Language Models
Spreadsheets, with their extensive two-dimensional grids, various layouts, and diverse formatting options, present notable challenges for large language models (LLMs). In response, we introduce SpreadsheetLLM, pioneering…
In-Context LearningTable DetectionTabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy
Tables contain factual and quantitative data accompanied by various structures and contents that pose challenges for machine comprehension. Previous methods generally design task-specific architectures and objectives for…
Language ModellingQuestion AnsweringReading ComprehensionTable Detection+1Vision Language Models for Spreadsheet Understanding: Challenges and Opportunities
This paper explores capabilities of Vision Language Models on spreadsheet comprehension. We propose three self-supervised challenges with corresponding evaluation metrics to comprehensively evaluate VLMs on Optical Chara…
Boundary DetectionOptical Character RecognitionOptical Character Recognition (OCR)Table DetectionSelective Fine-tuning on LLM-labeled Data May Reduce Reliance on Human Annotation: A Case Study Using Schedule-of-Event Table Detection
Large Language Models (LLMs) have demonstrated their efficacy across a broad spectrum of tasks in healthcare applications. However, often LLMs need to be fine-tuned on task-specific expert annotated data to achieve optim…
parameter-efficient fine-tuningTable DetectionEnd-to-End Semi-Supervised approach with Modulated Object Queries for Table Detection in Documents
Table detection, a pivotal task in document analysis, aims to precisely recognize and locate tables within document images. Although deep learning has shown remarkable progress in this realm, it typically requires an ext…
Table DetectionTowards End-to-End Semi-Supervised Table Detection with Semantic Aligned Matching Transformer
Table detection within document images is a crucial task in document processing, involving the identification and localization of tables. Recent strides in deep learning have substantially improved the accuracy of this t…
ObjectTable DetectionTC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content
The automatic recognition of tabular data in document images presents a significant challenge due to the diverse range of table styles and complex structures. Tables offer valuable content representation, enhancing the p…
Information RetrievalKnowledge GraphsOptical Character Recognition (OCR)Table Detection+1