Table Extraction

Table extraction focuses on automatically identifying and extracting tabular data from diverse sources like PDFs and images, aiming to convert unstructured information into structured, machine-readable formats. Current research emphasizes deep learning approaches, particularly leveraging transformer-based models and graph neural networks, to handle complex table structures, diverse layouts, and noisy data from OCR. This field is crucial for enabling efficient data analysis across various domains, from scientific literature mining and financial reporting to regulatory compliance, by unlocking the wealth of information locked within tabular data.