Ramen spoon eraser: CNN-based photo transformation for improving attractiveness of ramen photos

Abstract

In recent years, a large number of food photos are being posted globally on SNS. To obtain many views or "likes", attractive photos should be posted. However, some casual foods are served with utensils on a plate or a bowl at restaurants, which spoils attractiveness of meal photos. Especially in Japan where ramen noodle is the most popular casual food, ramen is usually served with a ramen spoon in a ramen bowl in a ramen noodle shop. This is a big problem for SNS photographers, because a ramen spoon soaked in a ramen bowl extremely degrades the appearance of ramen photos. Then, in this paper, we propose anapplication called "ramen spoon eraser" that erases a spoon from ramen photos with spoons using a CNN-based Image-to-Image translation network. In this application, it is possible to automatically erase ramen spoons from ramen photos, which extremely improve the attractiveness of ramen photos. In the experiment, we train models in two ways as CNN-based Image-to-Image translation networks with the dataset consisting of ramen images with / without spoons collected from the Web.