A Transfer Learning for Line-Based Portrait Sketch

Hyungbum Kim, Junyoung Oh and Heekyung Yang ()
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Hyungbum Kim: Department of Computer Science, Sangmyung University, Seoul 03016, Korea
Junyoung Oh: Department of Computer Science, Sangmyung University, Seoul 03016, Korea
Heekyung Yang: Division of SW Convergence, Sangmyung University, Seoul 03016, Korea

Mathematics, 2022, vol. 10, issue 20, 1-14

Abstract: This paper presents a transfer learning-based framework that produces line-based portrait sketch images from portraits. The proposed framework produces sketch images using a GAN architecture, which is trained through a pseudo-sketch image dataset. The pseudo-sketch image dataset is constructed from a single artist-created portrait sketch using a style transfer model with a series of postprocessing schemes. The proposed framework successfully produces portrait sketch images for portraits of various poses, expressions and illuminations. The excellence of the proposed model is proved by comparing the produced results with those from the existing works.

Keywords: sketch; transfer learning; portrait; GAN; AdaIN (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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