Page Level

Page-level analysis focuses on understanding the structure and content of individual pages within documents, aiming to improve automated document processing and information retrieval. Current research emphasizes the use of deep learning models, particularly transformer-based architectures and graph neural networks, to perform tasks such as layout analysis, text detection and recognition (including handwritten text), and page segmentation. These advancements are crucial for enhancing the accessibility and usability of digital documents, improving information extraction from complex layouts, and optimizing applications like e-commerce and visual question answering systems. The development of robust benchmarks and datasets is also a key area of focus, enabling more rigorous evaluation and comparison of different approaches.