MemeFaceGenerator: Adversarial Synthesis of Chinese Meme-face from Natural Sentences
Yifu Chen, Zongsheng Wang, Bowen Wu, Mengyuan Li, huan zhang, Lin Ma, Feng Liu, Qihang Feng, Baoxun Wang
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Chinese meme-face is a special kind of internet subculture widely spread in Chinese Social Community Networks. It usually consists of a template image modified by some amusing details and a text caption. In this paper, we present MemeFaceGenerator, a Generative Adversarial Network with the attention module and template information as supplementary signals, to automatically generate meme-faces from text inputs. We also develop a web service as system demonstration of meme-face synthesis. MemeFaceGenerator has been shown to be capable of generating high-quality meme-faces from random text inputs.