RecipeGen: A Benchmark for Real-World Recipe Image Generation
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Abstract (arXiv)
Recipe image generation is an important challenge in food computing, with applications from culinary education to interactive recipe platforms. However, there is currently no real-world dataset that comprehensively connects recipe goals, sequential steps, and corresponding images. To address this, we introduce RecipeGen, the first real-world goal-step-image benchmark for recipe generation, featuring diverse ingredients, varied recipe steps, multiple cooking styles, and a broad collection of food categories. Data is in https://github.com/zhangdaxia22/RecipeGen.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 26 references that are in the map. First posted on arXiv 7 Mar 2025.
Builds on
17 of 26 references.
References · 17
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- 2023FoodSAM: Any Food Segmentationcited by 19
5 more
- 2023FIRE: Food Image to REcipe generationcited by 18
- 2021Learning Structural Representations for Recipe Generation and Food Retrievalcited by 17
- 2020CookGAN: Meal Image Synthesis from Ingredientscited by 14
- 2024FoodSky: A Food-oriented Large Language Model that Passes the Chef and Dietetic Examinationcited by 10
- 2020Market2Dish: Health-aware Food Recommendationcited by 8
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Citing papers per year: 2025: 1.
1 paper.
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