2 citations · 4 across the 14 of their papers we have counts for
4 papers · 1 filter
Dr.3D: Adapting 3D GANs to Artistic Drawings
Wonjoon Jin, Nuri Ryu, Geonung Kim +2
While 3D GANs have recently demonstrated the high-quality synthesis of multi-view consistent images and 3D shapes, they are mainly restricted to photo-realistic human portraits. Th…
DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple Domains
Seongtae Kim, Kyoungkook Kang, Geonung Kim +2
Few-shot domain adaptation to multiple domains aims to learn a complex image distribution across multiple domains from a few training images. A naïve solution here is to train a se…
BigColor: Colorization using a Generative Color Prior for Natural Images
Geonung Kim, Kyoungkook Kang, Seongtae Kim +5
For realistic and vivid colorization, generative priors have recently been exploited. However, such generative priors often fail for in-the-wild complex images due to their limited…
Realistic Blur Synthesis for Learning Image Deblurring
Jaesung Rim, Geonung Kim, Jungeon Kim +3
Training learning-based deblurring methods demands a tremendous amount of blurred and sharp image pairs. Unfortunately, existing synthetic datasets are not realistic enough, and de…