2 papers
cs.CR2024
GLEAN: Generative Learning for Eliminating Adversarial Noise
Justin Lyu Kim, Kyoungwan Woo
In the age of powerful diffusion models such as DALL-E and Stable Diffusion, many in the digital art community have suffered style mimicry attacks due to fine-tuning these models o…
cs.CV2022
FREDSR: Fourier Residual Efficient Diffusive GAN for Single Image Super Resolution
Kyoungwan Woo, Achyuta Rajaram
FREDSR is a GAN variant that aims to outperform traditional GAN models in specific tasks such as Single Image Super Resolution with extreme parameter efficiency at the cost of per-…