Cross-modal food retrieval: Learning a joint embedding of food images and recipes with semantic consistency and attention mechanism

• Main Authors: WANG, Hao, SAHOO, Doyen, LIU, Chenghao, SHU, Ke, ACHANANUPARP, Palakorn, LIM, Ee-peng, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Correlation; Cross-Modal Retrieval; Data models; Deep Learning; Semantics; Sugar; Task analysis; Training; Visionand-Language; Visualization; Artificial Intelligence and Robotics; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6268; https://ink.library.smu.edu.sg/context/sis_research/article/7271/viewcontent/cross_modal_food_retrieval.pdf
• Institution: Singapore Management University

Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc. In this paper, we investigate cross-modal retrieval between food images and cook...