Table Recognition

Table recognition, the automated extraction of information from tabular data within images or documents, aims to accurately identify table structures and extract their content. Current research emphasizes end-to-end approaches using deep learning models, often incorporating transformers and multi-task learning to simultaneously handle table detection, structure recognition, and content extraction. These advancements are driven by the need for efficient processing of large-scale datasets and improved accuracy in handling diverse table formats, impacting fields like document analysis, data entry automation, and knowledge graph construction.