ICDAR 2019 competition on table detection and recognition (cTDaR)

L Gao, Y Huang, H Déjean, JL Meunier… - 2019 International …, 2019 - ieeexplore.ieee.org
The cTDaR competition aims at benchmarking state-of-the-art table detection (TRACK A)
and table recognition (TRACK B) methods. In particular, we wish to investigate and compare …

Tncr: Table net detection and classification dataset

A Abdallah, A Berendeyev, I Nuradin, D Nurseitov - Neurocomputing, 2022 - Elsevier
We present TNCR, a new table dataset with varying image quality collected from open
access websites. TNCR dataset can be used for table detection in scanned document …

A deep semantic segmentation model for image-based table structure recognition

Y Zou, J Ma - 2020 15th IEEE International Conference on …, 2020 - ieeexplore.ieee.org
Table structure recognition is a crucial step for automatic table information extraction. It is
conventional to utilize the features such as ruling lines or words for parsing the rows …

TC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content

A Anand, R Jaiswal, P Bhuyan, M Gupta… - Proceedings of the 1st …, 2023 - dl.acm.org
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 …

TableRocket: An Efficient and Effective Framework for Table Reconstruction

L Pang, Y Zhang, C Ma, Y Zhao, Y Zhou… - Chinese Conference on …, 2024 - Springer
Table reconstruction (TR) aims to extract cell contents and logical structure from table
images. Existing table reconstruction methods are superior in recognizing logical structure …

[PDF][PDF] TNCR: Table Net Detection and Classification Dataset

D Nurseitova - researchgate.net
We present TNCR, a new table dataset with varying image quality collected from open
access websites. TNCR dataset can be used for table detection in scanned document …