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MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Nowadays, driven by the increasing concern on diet and health, food computing has attracted enormous attention from both industry and research community. One of the most popular research topics in this domain is Food Retrieval, due to its profound influence on health-oriented applications. In this paper, we focus on the task of cross-modal retrieval between food images and cooking recipes. We present Modality-Consistent Embedding Network (MCEN) that learns modality-invariant representations by
doi:10.1109/cvpr42600.2020.01458
dblp:conf/cvpr/FuWLS20
fatcat:4ogf5xycfjfnji7t6rdnsxg2si