Scene Text Generation

Scene text generation focuses on computationally creating realistic images containing text within diverse scenes, aiming to improve the training data for scene text recognition models, particularly in low-resource languages. Current research heavily utilizes diffusion models, often enhanced with techniques like character-level encoding and attention mechanisms to control text placement and style, mitigating limitations of previous layout-dependent approaches. This research is significant because it addresses the scarcity of annotated data for training robust scene text recognition systems, ultimately impacting applications like document processing, image understanding, and multilingual text analysis.