The goal of multi-modal search is to obtain pertinent results from a database by utilizing a variety of modalities, including text and images. The multi-modal search aims to integrate several data kinds to deliver more thorough and accurate search results. This technique is widely used in e-commerce, healthcare, social media, and entertainment, among other fields. Machine learning methods, similarity metrics, feature extraction, and other approaches are needed for the multi-modal search. Due to the increasing availability of multi-modal data, multi-modal search has become a more important research topic in the domains of computer vision and information retrieval.