Image To Text Retrieval

Image-text retrieval refers to the task of retrieving relevant images based on textual descriptions or finding corresponding textual descriptions for given images. This task integrates computer vision and natural language processing technologies, with the main challenge being to bridge the semantic gap, which is the difference between the representation of visual data in images and the way humans describe this information using language. To address this, many methods focus on learning a shared embedding space where images and texts can be represented in a comparable manner, thus enabling the measurement of their similarity for more accurate retrieval. In the field of e-commerce, the application value of image-to-text retrieval is particularly significant, as it can enhance the precision of product search and recommendations.