Text Recognition

Text recognition, the automated extraction of text from images, aims to bridge the gap between visual and textual information. Current research focuses on improving accuracy and efficiency across diverse domains, including handwritten text, scene text (e.g., from signs or photographs), and documents, employing models like transformers and convolutional neural networks often enhanced by language models and self-supervised learning techniques. These advancements have significant implications for various applications, such as document digitization, automated data entry, and accessibility tools, while also driving innovation in related fields like visual document understanding and multimodal AI.