Image Tagging

Image tagging, the process of automatically assigning descriptive keywords to images, aims to bridge the gap between visual data and textual understanding. Current research focuses on developing robust models, often leveraging large vision-language models and incorporating multi-modal information (text and image) to improve accuracy and handle open-set scenarios (identifying tags not seen during training). These advancements are driven by the need for efficient image annotation in diverse applications, such as assisting visually impaired individuals, improving metadata management in large archives, and enhancing the performance of vision-language tasks. The development of more accurate and versatile image tagging models has significant implications for various fields, including cultural heritage preservation, accessibility technology, and computer vision research itself.