CookGAN: Meal Image Synthesis from Ingredients

@article{Han2020CookGANMI,
  title={CookGAN: Meal Image Synthesis from Ingredients},
  author={Fangda Han and Ricardo Guerrero and Vladimir Pavlovic},
  journal={2020 IEEE Winter Conference on Applications of Computer Vision (WACV)},
  year={2020},
  pages={1439-1447}
}
  • Fangda Han, Ricardo Guerrero, Vladimir Pavlovic
  • Published in
    IEEE Winter Conference on…
    2020
  • Computer Science, Mathematics
  • In this work we propose a new computational framework, based on generative deep models, for synthesis of photo-realistic food meal images from textual list of its ingredients. Previous works on synthesis of images from text typically rely on pre-trained text models to extract text features, followed by generative neural networks (GAN) aimed to generate realistic images conditioned on the text features. These works mainly focus on generating spatially compact and well-defined categories of… CONTINUE READING

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