Mask-based Food Image Synthesis with Cross-Modal Recipe Embeddings.

In this paper, we propose a Mask-based Recipe Embedding GAN (MRE-GAN), which enables us to generate a realistic food image based on a given mask image containing single or multiple food regions with cross-modal recipe embeddings for each food region. Thus, we can change meal shapes by modifying mask images, while by editing recipe text, we can change meal appearance. Our experimental findings confirmed that the proposed method could generate higher quality food images than the baselines, and we could change meal shapes and appearances by editing mask images and recipe texts as we liked.