Enhancing recipe retrieval with foundation models: A data augmentation perspective

• Main Authors: SONG, Fangzhou, ZHU, Bin, HAO, Yanbin, WANG, Shuo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Recipe retrieval; Data augmentation; Foundation models; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/9726; https://ink.library.smu.edu.sg/context/sis_research/article/10726/viewcontent/06751.pdf
• Institution: Singapore Management University

Learning recipe and food image representation in common embedding space is non-trivial but crucial for cross-modal recipe retrieval. In this paper, we propose a new perspective for this problem by utilizing foundation models for data augmentation. Leveraging on the remarkable capabilities of foundat...