Table Structure Recognition using Top-Down and Bottom-Up Cues

Sachin Raja; Ajoy Mondal; C V Jawahar

ECCV 2020poster122 citations

Table Structure Recognition using Top-Down and Bottom-Up Cues

Abstract

Tables are information-rich structured objects in document images. While significant work has been done in localizing tables as graphic objects in document images, only limited attempts exist on table structure recognition. Most existing literature on structure recognition depends on extraction of meta-features from the {\sc pdf} document or on the optical character recognition (OCR) models to extract low-level layout features from the image. However, these methods fail to generalize well because of the absence of meta-features or errors made by the OCR when there is a significant variance in table layouts and text organization. In our work, we focus on tables that have complex structures, dense content, and varying layouts with no dependency on meta-features and/or OCR.

BibTeX

@inproceedings{eccv2020_tablestructurere,
  title = {Table Structure Recognition using Top-Down and Bottom-Up Cues},
  author = {Sachin Raja and Ajoy Mondal and C V Jawahar},
  booktitle = {ECCV 2020},
  year = {2020}
}