# Image Colorization Using a Deep Convolutional Neural Network

arXiv: https://arxiv.org/abs/1604.07904 · HTML: https://mlsanity.com/paper/1604.07904/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2016.

## Built on by (most cited first, 1 of 1)

- [A Memory Efficient Deep Reinforcement Learning Approach For Snake Game Autonomous Agents](https://mlsanity.com/paper/2301.11977/) (2023)

## Abstract (arXiv)

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.