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cs.CV2024
Rethinking Image Skip Connections in StyleGAN2
Seung Park, Yong-Goo Shin
Various models based on StyleGAN have gained significant traction in the field of image synthesis, attributed to their robust training stability and superior performances. Within t…
cs.CV2020★ 2 cited
Generating Novel Glyph without Human Data by Learning to Communicate
Seung-won Park
In this paper, we present Neural Glyph, a system that generates novel glyph without any training data. The generator and the classifier are trained to communicate via visual symbol…