Layout Segmentation

Layout segmentation aims to automatically identify and delineate different structural elements within documents, such as text blocks, images, and tables, enabling machine understanding of document content and structure. Current research focuses on improving the robustness and generalization of layout segmentation models, often employing deep learning architectures like YOLO and Vision Transformers, and addressing data limitations through synthetic data generation and ensemble methods. This work is crucial for advancing document processing tasks such as OCR, information extraction, and digital archiving, impacting fields ranging from historical preservation to efficient data analysis.