Food recognition plays an important role in food choice and intake, which is essential to the
health and well‐being of humans. It is thus of importance to the computer vision community …

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 paper presents a solution to the challenge of mitigating carbon emissions from hosting
large-scale machine learning (ML) inference services. ML inference is critical to modern …

Cooking recipes are challenging to translate to robot plans as they feature rich linguistic
complexity, temporally-extended interconnected tasks, and an almost infinite space of …

Robotic chefs are a promising technology that can improve the availability of quality food by
reducing the time required for cooking, therefore decreasing food's overall cost. This paper …

Food computing has emerged as a prominent multidisciplinary field of research in recent
years. An ambitious goal of food computing is to develop end-to-end intelligent systems …

As people become more aware of their food choices, food computation models have
become increasingly popular in assisting people in maintaining healthy eating habits. For …

In the rapidly evolving landscape of online recipe sharing within a globalized context, there
has been a notable surge in research towards comprehending and generating food recipes …

Cross-modal recipe retrieval is an emerging visual-textual retrieval task, which aims at
matching food images with the corresponding recipes. Although large-scale Vision …

We present a new multimodal dataset called Visual Recipe Flow, which enables us to learn
each cooking action result in a recipe text. The dataset consists of object state changes and …