AgileGAN: stylizing portraits by inversion-consistent transfer learning

Portraiture as an art form has evolved from realistic depiction into a plethora of creative styles. While substantial progress has been made in automated stylization, generating high quality stylistic portraits is still a challenge, and even the recent popular Toonify suffers from several artifacts...

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Veröffentlicht in:	ACM transactions on graphics 2021-08, Vol.40 (4), p.1-13, Article 117
Hauptverfasser:	Song, Guoxian, Luo, Linjie, Liu, Jing, Ma, Wan-Chun, Lai, Chunpong, Zheng, Chuanxia, Cham, Tat-Jen
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer graphics Computing methodologies Non-photorealistic rendering Rendering
Online-Zugang:	Volltext
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