English

Evaluating Table Structure Recognition: A New Perspective

Computer Vision and Pattern Recognition 2022-08-02 v1 Machine Learning

Abstract

Existing metrics used to evaluate table structure recognition algorithms have shortcomings with regard to capturing text and empty cells alignment. In this paper, we build on prior work and propose a new metric - TEDS based IOU similarity (TEDS (IOU)) for table structure recognition which uses bounding boxes instead of text while simultaneously being robust against the above disadvantages. We demonstrate the effectiveness of our metric against previous metrics through various examples.

Cite

@article{arxiv.2208.00385,
  title  = {Evaluating Table Structure Recognition: A New Perspective},
  author = {Tarun Kumar and Himanshu Sharad Bhatt},
  journal= {arXiv preprint arXiv:2208.00385},
  year   = {2022}
}

Comments

4 pages, 2 figures, 1 table, 15th IAPR International Workshop on Document Analysis System (DAS 2022)

R2 v1 2026-06-25T01:21:30.860Z