Evaluating Table Structure Recognition: A New Perspective
Abstract
A new table structure recognition metric called TEDS (IOU) is proposed that uses bounding boxes to overcome limitations of existing metrics in handling text and empty cell alignment.
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.
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