Images & Recipes: Retrieval In The Cooking Context

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.

Stats

• citations2
• S2 citations—
• github stars0
• HF likes0
• heat score3.58
• arxiv keycarvalho2018images

Related papers

• Cross-modal Retrieval In The Cooking Context: Learning Semantic Text-image Embeddings (2018)0.00
• Recipe1m+: A Dataset For Learning Cross-modal Embeddings For Cooking Recipes And Food Images (2018)17.24
• Cross-modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism (2020)12.10
• Cross-lingual Adaptation For Recipe Retrieval With Mixup (2022)5.84
• CHEF: Cross-modal Hierarchical Embeddings For Food Domain Retrieval (2021)8.35
• Mitigating Cross-modal Representation Bias For Multicultural Image-to-recipe Retrieval (2025)0.00
• Learning Program Representations For Food Images And Cooking Recipes (2022)11.49
• SIMMER: Cross-modal Food Image--recipe Retrieval Via Mllm-based Embedding (2026)0.00