computer-vision-17
Table Recognition
3260 papers • 126 benchmarks • 313 datasets
Table recognition refers to the process of automatically identifying and extracting tabular structures from unstructured data sources such as text documents, images, or scanned documents. The goal of table recognition is to accurately detect the presence of tables within the data and extract their contents, including rows, columns, headers, and cell values.
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Benchmarks
These leaderboards are used to track progress in table-recognition-17
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PubTabNet
PubTabNet
ICDAR2013 table structure recognition
ICDAR2013 table structure recognition
WTW
Libraries
iUse these libraries to find table-recognition-17 models and implementations
3 papers 40,962
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No datasets available.
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