RecipeGen: A Benchmark for Real-World Recipe Image Generation
This addresses a gap in food computing for applications like culinary education and recipe platforms, but it is incremental as it focuses on dataset creation rather than novel methods.
The authors tackled the lack of a real-world dataset connecting recipe goals, steps, and images by introducing RecipeGen, a benchmark featuring diverse ingredients, steps, cooking styles, and food categories, with data available on GitHub.
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.