Real-Time Cooked Food Image Synthesis and Visual Cooking Progress Monitoring on Edge Devices

• URL: http://arxiv.org/abs/2511.16965v1
• Date: Fri, 21 Nov 2025 05:38:15 GMT
• Title: Real-Time Cooked Food Image Synthesis and Visual Cooking Progress Monitoring on Edge Devices
• Authors: Jigyasa Gupta, Soumya Goyal, Anil Kumar, Ishan Jindal,
• Abstract summary: We introduce the first oven-based cooking-progression dataset with chef-annotated doneness levels.<n>We propose an edge-efficient recipe and cooking state guided generator that synthesizes realistic food images conditioned on raw food image.
• Score: 4.373318192668093
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Synthesizing realistic cooked food images from raw inputs on edge devices is a challenging generative task, requiring models to capture complex changes in texture, color and structure during cooking. Existing image-to-image generation methods often produce unrealistic results or are too resource-intensive for edge deployment. We introduce the first oven-based cooking-progression dataset with chef-annotated doneness levels and propose an edge-efficient recipe and cooking state guided generator that synthesizes realistic food images conditioned on raw food image. This formulation enables user-preferred visual targets rather than fixed presets. To ensure temporal consistency and culinary plausibility, we introduce a domain-specific \textit{Culinary Image Similarity (CIS)} metric, which serves both as a training loss and a progress-monitoring signal. Our model outperforms existing baselines with significant reductions in FID scores (30\% improvement on our dataset; 60\% on public datasets)

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