{
  "id": "2203.17272",
  "version": "v1",
  "published": "2022-03-31T17:59:19.000Z",
  "updated": "2022-03-31T17:59:19.000Z",
  "title": "MyStyle: A Personalized Generative Prior",
  "authors": [
    "Yotam Nitzan",
    "Kfir Aberman",
    "Qiurui He",
    "Orly Liba",
    "Michal Yarom",
    "Yossi Gandelsman",
    "Inbar Mosseri",
    "Yael Pritch",
    "Daniel Cohen-or"
  ],
  "comment": "Project webpage: https://mystyle-personalized-prior.github.io/, Video: https://youtu.be/QvOdQR3tlOc",
  "categories": [
    "cs.CV",
    "cs.GR",
    "cs.LG"
  ],
  "abstract": "We introduce MyStyle, a personalized deep generative prior trained with a few shots of an individual. MyStyle allows to reconstruct, enhance and edit images of a specific person, such that the output is faithful to the person's key facial characteristics. Given a small reference set of portrait images of a person (~100), we tune the weights of a pretrained StyleGAN face generator to form a local, low-dimensional, personalized manifold in the latent space. We show that this manifold constitutes a personalized region that spans latent codes associated with diverse portrait images of the individual. Moreover, we demonstrate that we obtain a personalized generative prior, and propose a unified approach to apply it to various ill-posed image enhancement problems, such as inpainting and super-resolution, as well as semantic editing. Using the personalized generative prior we obtain outputs that exhibit high-fidelity to the input images and are also faithful to the key facial characteristics of the individual in the reference set. We demonstrate our method with fair-use images of numerous widely recognizable individuals for whom we have the prior knowledge for a qualitative evaluation of the expected outcome. We evaluate our approach against few-shots baselines and show that our personalized prior, quantitatively and qualitatively, outperforms state-of-the-art alternatives.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2022-03-31T17:59:19.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "personalized generative prior",
      "individual",
      "facial characteristics",
      "pretrained stylegan face generator",
      "small reference set"
    ],
    "tags": [
      "github project"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}