Cross-modal recipe retrieval via parallel- and cross-attention networks learning

Cross-modal recipe retrieval refers to the problem of retrieving a food image from a list of image candidates given a textual recipe as the query, or the reverse side. However, existing cross-modal recipe retrieval approaches mostly focus on learning the representations of images and recipes independently and sewing them up by projecting them into a common space. Such methods overlook the interplay between images and recipes, resulting in the suboptimal retrieval performance.