no code implementations • 28 Feb 2024 • Changho Choi, Minho Kim, Junhyeok Lee, Hyoung-Kyu Song, Younggeun Kim, Seungryong Kim
We show that our framework is applicable to other generators such as StyleNeRF, paving a way to 3D-aware face swapping and is also compatible with other downstream StyleGAN2 generator tasks.
1 code implementation • 20 Apr 2022 • Ki-Ung Song, Dongseok Shim, Kang-wook Kim, Jae-young Lee, Younggeun Kim
Super-resolution suffers from an innate ill-posed problem that a single low-resolution (LR) image can be from multiple high-resolution (HR) images.
3 code implementations • CVPR 2022 • Jeeseung Park, Younggeun Kim
We propose Styleformer, which is a style-based generator for GAN architecture, but a convolution-free transformer-based generator.
Ranked #6 on Image Generation on STL-10
2 code implementations • 6 Jun 2021 • Younggeun Kim, Donghee Son
Although SRFlow tried to account for ill-posed nature of the super-resolution by predicting multiple high-resolution images given a low-resolution image, there is room to improve the diversity and visual quality.