{
  "id": "1604.07904",
  "version": "v1",
  "published": "2016-04-27T02:16:43.000Z",
  "updated": "2016-04-27T02:16:43.000Z",
  "title": "Image Colorization Using a Deep Convolutional Neural Network",
  "authors": [
    "Tung Nguyen",
    "Kazuki Mori",
    "Ruck Thawonmas"
  ],
  "journal": "Proc. of ASIAGRAPH 2016, Toyama, Japan, pp. 49-50, Mar. 5-6, 2016",
  "categories": [
    "cs.CV",
    "cs.LG",
    "cs.NE"
  ],
  "abstract": "In this paper, we present a novel approach that uses deep learning techniques for colorizing grayscale images. By utilizing a pre-trained convolutional neural network, which is originally designed for image classification, we are able to separate content and style of different images and recombine them into a single image. We then propose a method that can add colors to a grayscale image by combining its content with style of a color image having semantic similarity with the grayscale one. As an application, to our knowledge the first of its kind, we use the proposed method to colorize images of ukiyo-e a genre of Japanese painting?and obtain interesting results, showing the potential of this method in the growing field of computer assisted art.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2016-04-27T02:16:43.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "I.2.6",
      "I.4.9",
      "J.5"
    ],
    "keywords": [
      "deep convolutional neural network",
      "image colorization",
      "pre-trained convolutional neural network",
      "deep learning techniques",
      "add colors"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}