Transformer achieves remarkable successes in understanding 1 and 2-dimensional signals
(eg, NLP and Image Content Understanding). As a potential alternative to convolutional …

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 …

Domain adaptation aims at improving the performance of learning tasks in a target domain
by leveraging the knowledge extracted from a source domain. To this end, one can perform …

The precise recognition of food categories plays a pivotal role for intelligent health
management, attracting significant research attention in recent years. Prominent …

In the food domain, text mining techniques are extensively employed to derive valuable
insights from large volumes of text data, facilitating applications such as aiding food recalls …

Current research in food analysis primarily concentrates on tasks such as food recognition,
recipe retrieval and nutrition estimation from a single image. Nevertheless, there is a …

Given the potential applications of generating recipes from food images, this area has
garnered significant attention from researchers in recent years. Existing works for recipe …

Cross-modal recipe retrieval has recently been explored for food recognition and
understanding. Text-rich recipe provides not only visual content information (eg, ingredients …

Cross-modal recipe retrieval has attracted research attention in recent years, thanks to the
availability of large-scale paired data for training. Nevertheless, obtaining adequate recipe …

Currently, food waste is a global concern, a problem that arises mainly at the consumption
level and generates environmental, economic, and social impacts. One way to reduce the …