We are pleased to welcome you to the 1st International Workshop on Multimedia for Cooking, Eating, and Related Applications (CEA++22) in conjunction with ACM Multimedia 2022.
Food is one of the central elements of our society. We eat a meal more than fifty thousand times while we are alive; enhancing the daily food experience impacts the quality of our life. There is a wide range of industries for supporting our eating activities. At the same time, however, there are many unsolved social problems, such as lifestyle-related diseases and sustainability. Technology-oriented solutions are vital since these social problems are often a trade-off with individual satisfaction.
Recent emerging technologies in multimedia, from mobile devices to deep learning technologies, have yielded many applications. Nonetheless, some problems are complicated to solve only by continuing the development of specialized technology because there are many stakeholders around our food-related activities. We aim to provide an opportunity for research groups concerning any food-related problem to discover each other, introduce their trials, and develop brave new ideas to solve their problems with multimedia technologies.
As a result of the call for applications, we received six long papers and six short papers from Japan, Norway, the United States, and China. The long papers were reviewed by at least three experts and the short papers by two experts, and the program committee decided to accept four long papers and five short papers. These papers provide new ideas for recipe/dish recommendation, mentality prediction from food records, cooking action recognition, food recognition, recipe analysis, and recipe editing assistance, with some new datasets. Note that we started a new trial of collecting works published recently to make the workshop a showcase of food-related studies. This year, we received two entries, which will be presented at the workshop.
Proceeding Downloads
Multimodal Dish Pairing: Predicting Side Dishes to Serve with a Main Dish
Planning a food menu is an essential task in our daily lives. We need to plan a menu by considering various perspectives. To reduce the burden when planning a menu, this study first tackles a novel problem of multimodal dish pairing (MDP), i.e., ...
Recipe Recommendation for Balancing Ingredient Preference and Daily Nutrients
In this work, we propose a recipe recommendation system for daily eating habits based on user preference and nutrient balance. This method prompts user input and allows for the substitution or addition of ingredients while reflecting the user's ...
Prediction of Mental State from Food Images
Diet is a very important factor in people's health management. Applications that record photos of meals and help people manage their diets are used by many users every day. In many cases, such applications use images just to estimate meals and calories. ...
Learning Sequential Transformation Information of Ingredients for Fine-Grained Cooking Activity Recognition
The goal of our research is to recognize the fine-grained cooking activities (e.g., dicing or mincing in cutting) in the egocentric videos from the sequential transformation of ingredients that are processed by the camera-wearer; these types of ...
Recipe Recording by Duplicating and Editing Standard Recipe
The best way to ascertain the exact nutritional value of a user's food intake is to have the user record the recipe for that food himself/herself. However, writing a recipe from scratch is tedious and impractical. Therefore, we proposed a method that ...
"Comparable Recipes": A Construction and Analysis of a Dataset of Recipes Described by Different People for the Same Dish
Recording high-quality textual recipes is effective for documenting food culture. However, comparing the quality of various recipes is difficult because recipe quality might depend on a variety of description styles and dishes. Therefore, we constructed ...
Few-shot Food Recognition with Pre-trained Model
Food recognition is a challenging task due to the diversity of food. However, conventional training in food recognition networks demands large amounts of labeled images, which is laborious and expensive. In this work, we aim to tackle the challenging ...
MIAIS: A Multimedia Recipe Dataset with Ingredient Annotation at Each Instructional Step
In this paper, we introduce a multimedia recipe dataset with annotation of ingredients at every instructional step, named MIAIS (Multimedia recipe dataset with Ingredient Annotation at every Instructional Step). One unique feature of recipe data is that ...
ABLE: Aesthetic Box Lunch Editing
This paper proposes an exploratory research that contains a pre-trained ordering recovery model to obtain correct placement sequences from box lunch images, and a generative adversarial network to composite novel box lunch presentations from single item ...
Creating a World Food Atlas
I face a problem multiple times every day: What am I going to eat, how much, and where? Where can I get enjoyable healthy food?
We live in a world where latest geo-spatial information of interest around us is available in the palm of our hand in our ...
CEA++2022 Panel - Toward Building a Global Food Network
How can we create a global food network?
Attempts are being made worldwide to lead people to healthier eating habits. They are not always in the academic field but often on a small scale and privately, in hospitals, nursing homes, schools, and various ...