Scene Text Recognition Model

Scene text recognition (STR) models aim to automatically extract textual information from images, a crucial task with applications ranging from sports video analysis to document processing. Current research focuses on improving accuracy and efficiency, particularly for low-resource languages and challenging scenarios like occluded text or diverse writing systems, often employing deep learning architectures such as CRNNs and more recent single visual models that bypass traditional sequential processing. These advancements are driven by the development of larger datasets, including synthetic data generation techniques, and the exploration of explainable AI methods to enhance model transparency and trustworthiness.