120 citations · 255 across the 11 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.CV2021
A Novel Generator with Auxiliary Branch for Improving GAN Performance
Seung Park, Yong-Goo Shin
The generator in the generative adversarial network (GAN) learns image generation in a coarse-to-fine manner in which earlier layers learn the overall structure of the image and th…
cs.CV2021★ 11 cited
Generative Convolution Layer for Image Generation
Seung Park, Yong-Goo Shin
This paper introduces a novel convolution method, called generative convolution (GConv), which is simple yet effective for improving the generative adversarial network (GAN) perfor…
cs.CV2021★ 30 cited
PConv: Simple yet Effective Convolutional Layer for Generative Adversarial Network
Seung Park, Yoon-Jae Yeo, Yong-Goo Shin
This paper presents a novel convolutional layer, called perturbed convolution (PConv), which focuses on achieving two goals simultaneously: improving the generative adversarial net…