articleDec 1, 2015Closed access

Deep Colorization

Shanghai Jiao Tong University · City University of Hong Kong

Indexed incrossref

Abstract

This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a very difficult problem and normally requires manual adjustment to achieve artifact-free quality. For instance, it normally requires human-labelled color scribbles on the grayscale target image or a careful selection of colorful reference images (e.g., capturing the same scene in the grayscale target image). Unlike the previous methods, this paper aims at a high-quality fully-automatic colorization method. With the assumption of a perfect patch matching technique, the use of an extremely large-scale reference database (that contains sufficient color images) is the most reliable solution to the…

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557
total citations
FWCI
19.84
Percentile
100%
References
39
Citations per year

Authors

3

Topics & keywords

Keywords
  • Grayscale
  • Computer science
  • Artificial intelligence
  • Computer vision
  • Artifact (error)
  • Noise (video)
  • Matching (statistics)
  • Image (mathematics)
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