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Table Detection
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Creating a Historical Migration Dataset from Finnish Church Records, 1800-1920
UniHDSA: A Unified Relation Prediction Approach for Hierarchical Document Structure Analysis
RAPTOR: Refined Approach for Product Table Object Recognition
CISOL: An Open and Extensible Dataset for Table Structure Recognition in the Construction Industry
TabSniper: Towards Accurate Table Detection & Structure Recognition for Bank Statements
A Comparative Study of PDF Parsing Tools Across Diverse Document Categories
SpreadsheetLLM: Encoding Spreadsheets for Large Language Models
TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy
Vision Language Models for Spreadsheet Understanding: Challenges and Opportunities
Selective Fine-tuning on LLM-labeled Data May Reduce Reliance on Human Annotation: A Case Study Using Schedule-of-Event Table Detection
End-to-End Semi-Supervised approach with Modulated Object Queries for Table Detection in Documents
Towards End-to-End Semi-Supervised Table Detection with Semantic Aligned Matching Transformer
TC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content
Enhancing Vision-Language Pre-training with Rich Supervisions
ClusterTabNet: Supervised clustering method for table detection and table structure recognition
TDeLTA: A Light-weight and Robust Table Detection Method based on Learning Text Arrangement
A Review On Table Recognition Based On Deep Learning
Table Detection for Visually Rich Document Images
Towards End-to-End Semi-Supervised Table Detection with Deformable Transformer
Revisiting Table Detection Datasets for Visually Rich Documents
TRACE: Table Reconstruction Aligned to Corner and Edges
A large-scale dataset for end-to-end table recognition in the wild
TRR360D: A dataset for 360 degree rotated rectangular box table detection
Aligning benchmark datasets for table structure recognition
CTE: A Dataset for Contextualized Table Extraction
Semantic Table Detection with LayoutLMv3
Deep learning for table detection and structure recognition: A survey
DATa: Domain Adaptation-Aided Deep Table Detection Using Visual-Lexical Representations
Table Detection in the Wild: A Novel Diverse Table Detection Dataset and Method
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural Networks
DEXTER: An end-to-end system to extract table contents from electronic medical health documents
Robust Table Detection and Structure Recognition from Heterogeneous Document Images
DiT: Self-supervised Pre-training for Document Image Transformer
On Cropped versus Uncropped Training Sets in Tabular Structure Detection
PubTables-1M: Towards comprehensive table extraction from unstructured documents
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