Table Detection

Table detection, a crucial task in document image analysis, aims to accurately identify and locate tables within diverse document types. Current research emphasizes improving the accuracy and efficiency of table detection using deep learning models, particularly transformer-based architectures like DETR and its variants, often incorporating semi-supervised learning techniques to reduce reliance on large labeled datasets. These advancements are driving progress in various applications, including automated data extraction, information retrieval, and knowledge graph construction, by enabling more robust and efficient processing of tabular data from diverse sources.