Images & Recipes: Retrieval in the cooking context

TL;DR

This paper presents a novel approach for large-scale image-recipe retrieval in the culinary domain, achieving state-of-the-art results on the Recipe1M dataset by aligning images with recipes.

Contribution

It introduces a new method for image-recipe alignment and demonstrates its effectiveness on a large-scale dataset, advancing computational cuisine applications.

Findings

Achieved state-of-the-art retrieval accuracy on Recipe1M dataset.

Validated the approach's effectiveness in large-scale culinary image-recipe matching.

Enhanced understanding of cross-modal retrieval in the cooking domain.

Abstract

Recent advances in the machine learning community allowed different use cases to emerge, as its association to domains like cooking which created the computational cuisine. In this paper, we tackle the picture-recipe alignment problem, having as target application the large-scale retrieval task (finding a recipe given a picture, and vice versa). Our approach is validated on the Recipe1M dataset, composed of one million image-recipe pairs and additional class information, for which we achieve state-of-the-art results.