Image to Text

Image-to-text research focuses on automatically generating textual descriptions from images, aiming to bridge the gap between visual and linguistic understanding. Current efforts concentrate on improving model accuracy and efficiency using transformer-based architectures, often incorporating techniques like vision grounding and hierarchical processing to better capture spatial relationships and semantic details within images. This field is significant for advancing multimodal AI, with applications ranging from automated image captioning and document understanding to assistive technologies for visually impaired individuals and enhanced accessibility in various digital contexts.