Table Structure Recognition

Table structure recognition (TSR) aims to automatically convert images of tables into machine-readable formats, facilitating data extraction and analysis from diverse document sources. Current research emphasizes improving the accuracy and efficiency of TSR models, focusing on architectures like transformers and object detection networks, often incorporating techniques such as self-supervised pre-training and uncertainty quantification to handle complex layouts and noisy data. Advances in TSR are crucial for automating document processing tasks across various fields, including scientific literature analysis, financial reporting, and information extraction from diverse digital archives.