A Transfer Learning for Line-Based Portrait Sketch

A Transfer Learning for Line-Based Portrait Sketch

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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 Lazy Susan 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 Nylon straps model is proved by comparing the produced results with those from the existing works.