Open AccessApplying GANs for Generating Image with Varied Facial Attributes from Sketch
Author(s) -
Warintorn Phusomsai,
Yachai Limpiyakorn
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1619/1/012013
Subject(s) - sketch , computer science , face (sociological concept) , image translation , artificial intelligence , image (mathematics) , translation (biology) , computer vision , identity (music) , image editing , computer graphics (images) , pattern recognition (psychology) , art , aesthetics , biology , algorithm , social science , biochemistry , sociology , messenger rna , gene
The rapid development of GANs and its variants has shown remarkable progress in synthesizing realistic images. Image-to-image translation becomes a potent research topic due to its wide application. The translation of face sketch to color images greatly contributes to digital image processing industry. It could also help confirm the identity of the suspect or lost persons. In this paper, a model is implemented by applying GANs for generating an image with varied facial attributes from sketch. The architecture consists of two separate GANs, implemented with Pix2Pix and StarGan2 as bases. The output realistic images can be generated with manipulating a single facial attribute including, wavy hair, straight hair, and wearing glasses.